Analisi sito web cnn.ai
Convolutional neural network - Wikipedia
Generato il Febbraio 05 2026 01:39 AM
Statistiche non aggiornate? AGGIORNA !
Il punteggio e 38/100
SEO Content
Title
Convolutional neural network - Wikipedia
Lunghezza : 40
Perfetto, il tuo title contiene tra 10 e 70 caratteri.
Description
Lunghezza : 0
Molto male. Non abbiamo trovato meta description nella tua pagina. Usa questo generatore online gratuito di meta tags per creare la descrizione.
Keywords
Molto male. Non abbiamo trovato meta keywords nella tua pagina. Usa questo generatore gratuito online di meta tags per creare keywords.
Og Meta Properties
Buono, questa pagina sfrutta i vantaggi Og Properties.
| Proprieta | Contenuto |
|---|---|
| title | Convolutional neural network - Wikipedia |
| type | website |
Headings
| H1 | H2 | H3 | H4 | H5 | H6 |
| 1 | 19 | 40 | 14 | 0 | 0 |
- [H1] Convolutional neural network
- [H2] Contents
- [H2] Architecture
- [H2] History
- [H2] Distinguishing features
- [H2] Building blocks
- [H2] Hyperparameters
- [H2] Translation equivariance and aliasing
- [H2] Evaluation
- [H2] Regularization methods
- [H2] Hierarchical coordinate frames
- [H2] Applications
- [H2] Fine-tuning
- [H2] Human interpretable explanations
- [H2] Related architectures
- [H2] Notable libraries
- [H2] See also
- [H2] Notes
- [H2] References
- [H2] External links
- [H3] Convolutional layers
- [H3] Pooling layers
- [H3] Fully connected layers
- [H3] Receptive field
- [H3] Weights
- [H3] Deconvolutional
- [H3] Receptive fields in the visual cortex
- [H3] Fukushima's analog threshold elements in a vision model
- [H3] Neocognitron, origin of the trainable CNN architecture
- [H3] Convolution in time
- [H3] Time delay neural networks
- [H3] Image recognition with CNNs trained by gradient descent
- [H3] Shift-invariant neural network
- [H3] GPU implementations
- [H3] Convolutional layer
- [H3] Pooling layer
- [H3] ReLU layer
- [H3] Fully connected layer
- [H3] Loss layer
- [H3] Padding
- [H3] Stride
- [H3] Number of filters
- [H3] Filter (or kernel) size
- [H3] Pooling type and size
- [H3] Dilation
- [H3] Empirical
- [H3] Explicit
- [H3] Image recognition
- [H3] Video analysis
- [H3] Natural language processing
- [H3] Animal behavior detection
- [H3] Anomaly detection
- [H3] Drug discovery
- [H3] Checkers game
- [H3] Go
- [H3] Time series forecasting
- [H3] Cultural heritage and 3D-datasets
- [H3] Deep Q-networks
- [H3] Deep belief networks
- [H3] Neural abstraction pyramid
- [H4] Max pooling
- [H4] LeNet-5
- [H4] Local connectivity
- [H4] Spatial arrangement
- [H4] Parameter sharing
- [H4] Channel max pooling
- [H4] Dropout
- [H4] DropConnect
- [H4] Stochastic pooling
- [H4] Artificial data
- [H4] Early stopping
- [H4] Number of parameters
- [H4] Weight decay
- [H4] Max norm constraints
Images
Abbiamo trovato 50 immagini in questa pagina web.
13 attributi alt sono vuoti o mancanti. Aggiungi testo alternativo in modo tale che i motori di ricerca possano comprendere meglio il contenuto delle tue immagini.
Text/HTML Ratio
Ratio : 0%
Il rapporto testo/codice HTML di questa pagina e inferiore a 15 percento, questo significa che il tuo sito web necessita probabilmente di molto piu contenuto.
Flash
Perfetto, non e stato rilevato contenuto Flash in questa pagina.
Iframe
Grande, non sono stati rilevati Iframes in questa pagina.
SEO Links
URL Rewrite
Male. I tuoi links hanno query string.
Underscores in the URLs
Abbiamo rilevato underscores nei tuoi URLs. Dovresti utilizzare trattini per ottimizzare le pagine per il tuo SEO.
In-page links
Abbiamo trovato un totale di 1142 links inclusi 226 link(s) a files
| Anchor | Type | Juice |
|---|---|---|
| Jump to content | Interno | Passing Juice |
| Edit links | Externo | Passing Juice |
| Machine learning | Interno | Passing Juice |
| data mining | Interno | Passing Juice |
| Supervised learning | Interno | Passing Juice |
| Unsupervised learning | Interno | Passing Juice |
| Semi-supervised learning | Interno | Passing Juice |
| Self-supervised learning | Interno | Passing Juice |
| Reinforcement learning | Interno | Passing Juice |
| Meta-learning | Interno | Passing Juice |
| Online learning | Interno | Passing Juice |
| Batch learning | Interno | Passing Juice |
| Curriculum learning | Interno | Passing Juice |
| Rule-based learning | Interno | Passing Juice |
| Neuro-symbolic AI | Interno | Passing Juice |
| Neuromorphic engineering | Interno | Passing Juice |
| Quantum machine learning | Interno | Passing Juice |
| Classification | Interno | Passing Juice |
| Generative modeling | Interno | Passing Juice |
| Regression | Interno | Passing Juice |
| Clustering | Interno | Passing Juice |
| Dimensionality reduction | Interno | Passing Juice |
| Density estimation | Interno | Passing Juice |
| Anomaly detection | Interno | Passing Juice |
| Data cleaning | Interno | Passing Juice |
| AutoML | Interno | Passing Juice |
| Association rules | Interno | Passing Juice |
| Semantic analysis | Interno | Passing Juice |
| Structured prediction | Interno | Passing Juice |
| Feature engineering | Interno | Passing Juice |
| Feature learning | Interno | Passing Juice |
| Learning to rank | Interno | Passing Juice |
| Grammar induction | Interno | Passing Juice |
| Ontology learning | Interno | Passing Juice |
| Multimodal learning | Interno | Passing Juice |
| Apprenticeship learning | Interno | Passing Juice |
| Decision trees | Interno | Passing Juice |
| Ensembles | Interno | Passing Juice |
| Bagging | Interno | Passing Juice |
| Boosting | Interno | Passing Juice |
| Random forest | Interno | Passing Juice |
| Linear regression | Interno | Passing Juice |
| Naive Bayes | Interno | Passing Juice |
| Artificial neural networks | Interno | Passing Juice |
| Logistic regression | Interno | Passing Juice |
| Perceptron | Interno | Passing Juice |
| Relevance vector machine (RVM) | Interno | Passing Juice |
| Support vector machine (SVM) | Interno | Passing Juice |
| BIRCH | Interno | Passing Juice |
| CURE | Interno | Passing Juice |
| Hierarchical | Interno | Passing Juice |
| Fuzzy | Interno | Passing Juice |
| Expectation–maximization (EM) | Interno | Passing Juice |
| DBSCAN | Interno | Passing Juice |
| OPTICS | Interno | Passing Juice |
| Mean shift | Interno | Passing Juice |
| Factor analysis | Interno | Passing Juice |
| CCA | Interno | Passing Juice |
| ICA | Interno | Passing Juice |
| LDA | Interno | Passing Juice |
| NMF | Interno | Passing Juice |
| PCA | Interno | Passing Juice |
| PGD | Interno | Passing Juice |
| t-SNE | Interno | Passing Juice |
| SDL | Interno | Passing Juice |
| Graphical models | Interno | Passing Juice |
| Bayes net | Interno | Passing Juice |
| Conditional random field | Interno | Passing Juice |
| Hidden Markov | Interno | Passing Juice |
| RANSAC | Interno | Passing Juice |
| Local outlier factor | Interno | Passing Juice |
| Isolation forest | Interno | Passing Juice |
| Neural networks | Interno | Passing Juice |
| Autoencoder | Interno | Passing Juice |
| Deep learning | Interno | Passing Juice |
| Feedforward neural network | Interno | Passing Juice |
| Recurrent neural network | Interno | Passing Juice |
| LSTM | Interno | Passing Juice |
| GRU | Interno | Passing Juice |
| ESN | Interno | Passing Juice |
| reservoir computing | Interno | Passing Juice |
| Boltzmann machine | Interno | Passing Juice |
| Restricted | Interno | Passing Juice |
| GAN | Interno | Passing Juice |
| Diffusion model | Interno | Passing Juice |
| SOM | Interno | Passing Juice |
| U-Net | Interno | Passing Juice |
| LeNet | Interno | Passing Juice |
| AlexNet | Interno | Passing Juice |
| DeepDream | Interno | Passing Juice |
| Neural field | Interno | Passing Juice |
| Neural radiance field | Interno | Passing Juice |
| Physics-informed neural networks | Interno | Passing Juice |
| Transformer | Interno | Passing Juice |
| Vision | Interno | Passing Juice |
| Mamba | Interno | Passing Juice |
| Spiking neural network | Interno | Passing Juice |
| Memtransistor | Interno | Passing Juice |
| Electrochemical RAM | Interno | Passing Juice |
| Q-learning | Interno | Passing Juice |
| Policy gradient | Interno | Passing Juice |
| SARSA | Interno | Passing Juice |
| Temporal difference (TD) | Interno | Passing Juice |
| Multi-agent | Interno | Passing Juice |
| Self-play | Interno | Passing Juice |
| Active learning | Interno | Passing Juice |
| Crowdsourcing | Interno | Passing Juice |
| Human-in-the-loop | Interno | Passing Juice |
| Mechanistic interpretability | Interno | Passing Juice |
| RLHF | Interno | Passing Juice |
| Coefficient of determination | Interno | Passing Juice |
| Confusion matrix | Interno | Passing Juice |
| Learning curve | Interno | Passing Juice |
| ROC curve | Interno | Passing Juice |
| Kernel machines | Interno | Passing Juice |
| Bias–variance tradeoff | Interno | Passing Juice |
| Computational learning theory | Interno | Passing Juice |
| Empirical risk minimization | Interno | Passing Juice |
| Occam learning | Interno | Passing Juice |
| PAC learning | Interno | Passing Juice |
| Statistical learning | Interno | Passing Juice |
| VC theory | Interno | Passing Juice |
| Topological deep learning | Interno | Passing Juice |
| AAAI | Interno | Passing Juice |
| ECML PKDD | Interno | Passing Juice |
| NeurIPS | Interno | Passing Juice |
| ICML | Interno | Passing Juice |
| ICLR | Interno | Passing Juice |
| IJCAI | Interno | Passing Juice |
| ML | Interno | Passing Juice |
| JMLR | Interno | Passing Juice |
| Glossary of artificial intelligence | Interno | Passing Juice |
| List of datasets for machine-learning research | Interno | Passing Juice |
| List of datasets in computer vision and image processing | Interno | Passing Juice |
| Outline of machine learning | Interno | Passing Juice |
| kernel | Interno | Passing Juice |
| predictions | Interno | Passing Juice |
| computer vision | Interno | Passing Juice |
| image processing | Interno | Passing Juice |
| transformer | Interno | Passing Juice |
| Vanishing gradients | Interno | Passing Juice |
| backpropagation | Interno | Passing Juice |
| regularization | Interno | Passing Juice |
| recommender systems | Interno | Passing Juice |
| image classification | Interno | Passing Juice |
| image segmentation | Interno | Passing Juice |
| medical image analysis | Interno | Passing Juice |
| natural language processing | Interno | Passing Juice |
| brain–computer interfaces | Interno | Passing Juice |
| time series | Interno | Passing Juice |
| convolution | Interno | Passing Juice |
| equivariant | Interno | Passing Juice |
| invariant to translation | Interno | Passing Juice |
| layer | Interno | Passing Juice |
| overfitting | Interno | Passing Juice |
| inspired | Interno | Passing Juice |
| biological | Interno | Passing Juice |
| neurons | Interno | Passing Juice |
| visual cortex | Interno | Passing Juice |
| cortical neurons | Interno | Passing Juice |
| visual field | Interno | Passing Juice |
| receptive field | Interno | Passing Juice |
| hidden layers | Interno | Passing Juice |
| dot product | Interno | Passing Juice |
| Frobenius inner product | Interno | Passing Juice |
| ReLU | Interno | Passing Juice |
| pooling layers | Interno | Passing Juice |
| matched filter | Interno | Passing Juice |
| tensor | Interno | Passing Juice |
| channels | Interno | Passing Juice |
| fully connected feedforward neural networks | Interno | Passing Juice |
| features | Interno | Passing Juice |
| memory footprint | Interno | Passing Juice |
| organisms | Interno | Passing Juice |
| Surround suppression | Interno | Passing Juice |
| Hubel | Interno | Passing Juice |
| Wiesel | Interno | Passing Juice |
| simple cells | Interno | Passing Juice |
| complex cells | Interno | Passing Juice |
| Kunihiko Fukushima | Interno | Passing Juice |
| activation function | Interno | Passing Juice |
| neocognitron | Interno | Passing Juice |
| signal-processing concept of a filter | Interno | Passing Juice |
| time delay neural network | Interno | Passing Juice |
| Alex Waibel | Interno | Passing Juice |
| ZIP Code | Interno | Passing Juice |
| Yann LeCun | Interno | Passing Juice |
| syllable | Interno | Passing Juice |
| checks | Interno | Passing Juice |
| NCR | Interno | Passing Juice |
| mammograms (1994) | Interno | Passing Juice |
| electromyography | Interno | Passing Juice |
| graphics processing units | Interno | Passing Juice |
| CPU | Interno | Passing Juice |
| GPGPU | Interno | Passing Juice |
| deep belief networks | Interno | Passing Juice |
| IDSIA | Interno | Passing Juice |
| ImageNet Large Scale Visual Recognition Challenge | Interno | Passing Juice |
| AI boom | Interno | Passing Juice |
| GPUs | Interno | Passing Juice |
| SIMD | Interno | Passing Juice |
| Intel Xeon Phi | Interno | Passing Juice |
| curse of dimensionality | Interno | Passing Juice |
| RGB color | Interno | Passing Juice |
| CIFAR-10 | Interno | Passing Juice |
| locality of reference | Interno | Passing Juice |
| spatially local | Interno | Passing Juice |
| 3 dimensions | Interno | Passing Juice |
| translational invariance | Interno | Passing Juice |
| free parameters | Interno | Passing Juice |
| discrete Laplacian operator | Interno | Passing Juice |
| sparse local connectivity | Interno | Passing Juice |
| hyperparameter | Interno | Passing Juice |
| hyperparameters | Interno | Passing Juice |
| stride | Interno | Passing Juice |
| overlapping | Interno | Passing Juice |
| integer | Interno | Passing Juice |
| symmetric | Interno | Passing Juice |
| down-sampling | Interno | Passing Juice |
| partitions | Interno | Passing Juice |
| ReLU layer | Interno | Passing Juice |
| max operation | Interno | Passing Juice |
| average | Interno | Passing Juice |
| Alston Householder | Interno | Passing Juice |
| nonlinearity | Interno | Passing Juice |
| decision function | Interno | Passing Juice |
| Yoshua Bengio | Interno | Passing Juice |
| hyperbolic tangent | Interno | Passing Juice |
| sigmoid function | Interno | Passing Juice |
| generalization | Interno | Passing Juice |
| affine transformation | Interno | Passing Juice |
| matrix multiplication | Interno | Passing Juice |
| vector addition | Interno | Passing Juice |
| Loss function | Interno | Passing Juice |
| Loss functions for classification | Interno | Passing Juice |
| training | Interno | Passing Juice |
| true | Interno | Passing Juice |
| Softmax | Interno | Passing Juice |
| cross-entropy | Interno | Passing Juice |
| Euclidean | Interno | Passing Juice |
| regressing | Interno | Passing Juice |
| real-valued | Interno | Passing Juice |
| verification | Interno | Passing Juice |
| improve this article | Interno | Passing Juice |
| adding citations to reliable sources | Interno | Passing Juice |
| Learn how and when to remove this message | Interno | Passing Juice |
| Inceptionv3 | Interno | Passing Juice |
| Max pooling | Interno | Passing Juice |
| information loss | Interno | Passing Juice |
| Nyquist–Shannon sampling theorem | Interno | Passing Juice |
| aliasing | Interno | Passing Juice |
| anti-aliasing | Interno | Passing Juice |
| data augmentation | Interno | Passing Juice |
| capsule neural networks | Interno | Passing Juice |
| conformal prediction | Interno | Passing Juice |
| ill-posed problem | Interno | Passing Juice |
| dropout | Interno | Passing Juice |
| expected value | Interno | Passing Juice |
| deep neural networks | Interno | Passing Juice |
| deterministic | Interno | Passing Juice |
| multinomial distribution | Interno | Passing Juice |
| deformations | Interno | Passing Juice |
| elastic deformations | Interno | Passing Juice |
| MNIST data set | Interno | Passing Juice |
| Early stopping | Interno | Passing Juice |
| zero norm | Interno | Passing Juice |
| L1 norm | Interno | Passing Juice |
| L2 norm | Interno | Passing Juice |
| elastic net regularization | Interno | Passing Juice |
| projected gradient descent | Interno | Passing Juice |
| retina | Interno | Passing Juice |
| visual system | Interno | Passing Juice |
| image recognition | Interno | Passing Juice |
| error rate | Interno | Passing Juice |
| facial recognition | Interno | Passing Juice |
| video quality | Interno | Passing Juice |
| root mean square error | Interno | Passing Juice |
| GoogLeNet | Interno | Passing Juice |
| precision | Interno | Passing Juice |
| text-to-video model | Interno | Passing Juice |
| semantic parsing | Interno | Passing Juice |
| recurrent neural networks | Interno | Passing Juice |
| drug discovery | Interno | Passing Juice |
| proteins | Interno | Passing Juice |
| structure-based drug design | Interno | Passing Juice |
| aromaticity | Interno | Passing Juice |
| hydrogen bonding | Interno | Passing Juice |
| biomolecules | Interno | Passing Juice |
| Ebola virus | Interno | Passing Juice |
| multiple sclerosis | Interno | Passing Juice |
| checkers | Interno | Passing Juice |
| Fogel | Interno | Passing Juice |
| Blondie24 | Interno | Passing Juice |
| Chinook | Interno | Passing Juice |
| computer Go | Interno | Passing Juice |
| Storkey | Interno | Passing Juice |
| GNU Go | Interno | Passing Juice |
| Monte Carlo tree search | Interno | Passing Juice |
| 6 dan | Interno | Passing Juice |
| AlphaGo | Interno | Passing Juice |
| clay tablets | Interno | Passing Juice |
| cuneiform writing | Interno | Passing Juice |
| 3D scanners | Interno | Passing Juice |
| GigaMesh Software Framework | Interno | Passing Juice |
| curvature | Interno | Passing Juice |
| transfer learning | Interno | Passing Juice |
| critical systems | Interno | Passing Juice |
| self-driving cars | Interno | Passing Juice |
| visual salience | Interno | Passing Juice |
| spatial attention | Interno | Passing Juice |
| temporal attention | Interno | Passing Juice |
| Atari 2600 | Interno | Passing Juice |
| Convolutional deep belief networks | Interno | Passing Juice |
| Caffe | Interno | Passing Juice |
| C++ | Interno | Passing Juice |
| Python | Interno | Passing Juice |
| MATLAB | Interno | Passing Juice |
| Deeplearning4j | Interno | Passing Juice |
| Java | Interno | Passing Juice |
| Scala | Interno | Passing Juice |
| Spark | Interno | Passing Juice |
| Dlib | Interno | Passing Juice |
| Microsoft Cognitive Toolkit | Interno | Passing Juice |
| C# | Interno | Passing Juice |
| TensorFlow | Interno | Passing Juice |
| Apache 2.0 | Interno | Passing Juice |
| tensor processing unit | Interno | Passing Juice |
| Theano | Interno | Passing Juice |
| NumPy | Interno | Passing Juice |
| CUDA | Interno | Passing Juice |
| on-the-GPU | Interno | Passing Juice |
| Torch | Interno | Passing Juice |
| scientific computing | Interno | Passing Juice |
| C | Interno | Passing Juice |
| Lua | Interno | Passing Juice |
| Attention (machine learning) | Interno | Passing Juice |
| Natural-language processing | Interno | Passing Juice |
| Scale-invariant feature transform | Interno | Passing Juice |
| Vision processing unit | Interno | Passing Juice |
| ^ | Interno | Passing Juice |
| time domain | Interno | Passing Juice |
| frequency domain | Interno | Passing Juice |
| mathematical spaces | Interno | Passing Juice |
| ^ | Interno | Passing Juice |
| ^ | Interno | Passing Juice |
| categorical data | Interno | Passing Juice |
| ^ | Interno | Passing Juice |
| "Deep learning" | Externo | noFollow |
| Bibcode | Interno | Passing Juice |
| 2015Natur.521..436L | Externo | noFollow |
| doi | Interno | Passing Juice |
| 10.1038/nature14539 | Externo | noFollow |
| ISSN | Interno | Passing Juice |
| 1476-4687 | Externo | noFollow |
| PMID | Interno | Passing Juice |
| 26017442 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "Backpropagation Applied to Handwritten Zip Code Recognition" | Externo | noFollow |
| 10.1162/neco.1989.1.4.541 | Externo | noFollow |
| 0899-7667 | Externo | noFollow |
| ISBN | Interno | Passing Juice |
| Archived | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 2020ITII...16.5769Z | Externo | noFollow |
| 10.1109/TII.2019.2956078 | Externo | noFollow |
| 1941-0050 | Externo | noFollow |
| S2CID | Interno | Passing Juice |
| 213010088 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "Residue Number System-Based Solution for Reducing the Hardware Cost of a Convolutional Neural Network" | Externo | noFollow |
| 10.1016/j.neucom.2020.04.018 | Externo | noFollow |
| 219470398 | Externo | noFollow |
| Archived | Externo | noFollow |
| OCLC | Interno | Passing Juice |
| 987790957 | Externo | noFollow |
| "An Artificial Neural Network for Spatio-Temporal Bipolar Patterns: Application to Phoneme Classification" | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 10.1016/j.matcom.2020.04.031 | Externo | noFollow |
| 0378-4754 | Externo | noFollow |
| 218955622 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 10.1145/1390156.1390177 | Externo | noFollow |
| 2617020 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "Deep Learning Techniques to Improve Intraoperative Awareness Detection from Electroencephalographic Signals" | Externo | noFollow |
| 10.1109/EMBC44109.2020.9176228 | Externo | noFollow |
| 33017950 | Externo | noFollow |
| 221386616 | Externo | noFollow |
| Archived | Externo | noFollow |
| 10.1109/CBI.2017.23 | Externo | noFollow |
| 4950757 | Externo | noFollow |
| "Shift-invariant pattern recognition neural network and its optical architecture" | Externo | noFollow |
| Archived | Externo | noFollow |
| "Parallel distributed processing model with local space-invariant interconnections and its optical architecture" | Externo | noFollow |
| 1990ApOpt..29.4790Z | Externo | noFollow |
| 10.1364/AO.29.004790 | Externo | noFollow |
| 20577468 | Externo | noFollow |
| Archived | Externo | noFollow |
| "Stride and Translation Invariance in CNNs" | Externo | noFollow |
| arXiv | Interno | Passing Juice |
| 2103.10097 | Externo | noFollow |
| 10.1007/978-3-030-66151-9_17 | Externo | noFollow |
| 232269854 | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "Hidden bias in the DUD-E dataset leads to misleading performance of deep learning in structure-based virtual screening" | Externo | noFollow |
| 2019PLoSO..1420113C | Externo | noFollow |
| 10.1371/journal.pone.0220113 | Externo | noFollow |
| PMC | Interno | Passing Juice |
| 31430292 | Externo | noFollow |
| "Neocognitron" | Externo | noFollow |
| 2007SchpJ...2.1717F | Externo | noFollow |
| "Receptive fields and functional architecture of monkey striate cortex" | Externo | noFollow |
| 10.1113/jphysiol.1968.sp008455 | Externo | noFollow |
| 0022-3751 | Externo | noFollow |
| 4966457 | Externo | noFollow |
| "Neocognitron: A Self-organizing Neural Network Model for a Mechanism of Pattern Recognition Unaffected by Shift in Position" | Externo | noFollow |
| 10.1007/BF00344251 | Externo | noFollow |
| 7370364 | Externo | noFollow |
| 206775608 | Externo | noFollow |
| Archived | Externo | noFollow |
| "Subject independent facial expression recognition with robust face detection using a convolutional neural network" | Externo | noFollow |
| 2003NN.....16..555M | Externo | noFollow |
| 10.1016/S0893-6080(03)00115-1 | Externo | noFollow |
| 12850007 | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| https://arxiv.org/abs/2108.11663v3 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "Convolutional Neural Networks (LeNet) – DeepLearning 0.1 documentation" | Externo | noFollow |
| the original | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 1610.02357 | Externo | noFollow |
| cs.CV | Externo | noFollow |
| "Flexible, High Performance Convolutional Neural Networks for Image Classification" | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| Krizhevsky | Interno | Passing Juice |
| "ImageNet Classification with Deep Convolutional Neural Networks" | Externo | noFollow |
| Archived | Externo | noFollow |
| the original | Externo | noFollow |
| Institute of Electrical and Electronics Engineers | Interno | Passing Juice |
| 1202.2745 | Externo | noFollow |
| CiteSeerX | Interno | Passing Juice |
| 10.1.1.300.3283 | Externo | noFollow |
| 10.1109/CVPR.2012.6248110 | Externo | noFollow |
| 812295155 | Externo | noFollow |
| 2161592 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 1511.07122 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 1706.05587 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 2108.07387 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "LeNet-5, convolutional neural networks" | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "Adaptive deconvolutional networks for mid and high level feature learning" | Externo | noFollow |
| 10.1109/iccv.2011.6126474 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 1603.07285 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "Deconvolution and Checkerboard Artifacts" | Externo | noFollow |
| 10.23915/distill.00003 | Externo | noFollow |
| 2476-0757 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "Comparing Object Recognition in Humans and Deep Convolutional Neural Networks—An Eye Tracking Study" | Externo | noFollow |
| 10.3389/fnins.2021.750639 | Externo | noFollow |
| 1662-453X | Externo | noFollow |
| 34690686 | Externo | noFollow |
| "Receptive fields of single neurones in the cat's striate cortex" | Externo | noFollow |
| 10.1113/jphysiol.1959.sp006308 | Externo | noFollow |
| 14403679 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| Archived | Externo | noFollow |
| 1969ITSSC...5..322F | Externo | noFollow |
| 10.1109/TSSC.1969.300225 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| Schmidhuber, Juergen | Interno | Passing Juice |
| 2212.11279 | Externo | noFollow |
| cs.NE | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "Deep learning" | Externo | noFollow |
| 3074096 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 1710.05941 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| Phoneme Recognition Using Time-Delay Neural Networks | Externo | noFollow |
| Archived | Externo | noFollow |
| Wayback Machine | Interno | Passing Juice |
| ^ | Interno | Passing Juice |
| "Convolutional networks for images, speech, and time series" | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| Connectionist Architectures for Multi-Speaker Phoneme Recognition | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| Neural network recognizer for hand-written zip code digits | Externo | noFollow |
| Archived | Externo | noFollow |
| Backpropagation Applied to Handwritten Zip Code Recognition | Externo | noFollow |
| Archived | Externo | noFollow |
| "Image processing of human corneal endothelium based on a learning network" | Externo | noFollow |
| 1991ApOpt..30.4211Z | Externo | noFollow |
| 10.1364/AO.30.004211 | Externo | noFollow |
| 20706526 | Externo | noFollow |
| Archived | Externo | noFollow |
| "Computerized detection of clustered microcalcifications in digital mammograms using a shift-invariant artificial neural network" | Externo | noFollow |
| 1994MedPh..21..517Z | Externo | noFollow |
| 10.1118/1.597177 | Externo | noFollow |
| 8058017 | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 10.1109/ICCV.1993.378228 | Externo | noFollow |
| 8619176 | Externo | noFollow |
| "Deep Learning" | Externo | noFollow |
| 10.1.1.76.1541 | Externo | noFollow |
| 10.1162/neco.2006.18.7.1527 | Externo | noFollow |
| 16764513 | Externo | noFollow |
| 2309950 | Externo | noFollow |
| Archived | Externo | noFollow |
| 10.1142/2808 | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 1998IEEEP..86.2278L | Externo | noFollow |
| 10.1109/5.726791 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "Error Back Propagation with Minimum-Entropy Weights: A Technique for Better Generalization of 2-D Shift-Invariant NNs" | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| Applications of neural networks to medical signal processing | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| Decomposition of surface EMG signals into single fiber action potentials by means of neural network | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| Identification of firing patterns of neuronal signals | Externo | noFollow |
| https://ieeexplore.ieee.org/document/70115 | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 2004PatRe..37.1311O | Externo | noFollow |
| 10.1016/j.patcog.2004.01.013 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "Using GPUs for Machine Learning Algorithms" | Externo | noFollow |
| 10.1109/ICDAR.2005.251 | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "High Performance Convolutional Neural Networks for Document Processing" | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| ^ | Interno | Passing Juice |
| "Greedy Layer-Wise Training of Deep Networks" | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "Efficient Learning of Sparse Representations with an Energy-Based Model" | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "Large-scale deep unsupervised learning using graphics processors" | Externo | noFollow |
| 10.1145/1553374.1553486 | Externo | noFollow |
| 392458 | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 1003.0358 | Externo | noFollow |
| 2010NeCom..22.3207C | Externo | noFollow |
| 10.1162/NECO_a_00052 | Externo | noFollow |
| 20858131 | Externo | noFollow |
| 1918673 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "IJCNN 2011 Competition result table" | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "History of computer vision contests won by deep CNNs on GPU" | Externo | noFollow |
| Archived | Externo | noFollow |
| "ImageNet classification with deep convolutional neural networks" | Externo | noFollow |
| 10.1145/3065386 | Externo | noFollow |
| 0001-0782 | Externo | noFollow |
| 195908774 | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 1702.07908 | Externo | noFollow |
| 10.1007/s11227-017-1994-x | Externo | noFollow |
| 14135321 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "The Potential of the Intel (R) Xeon Phi for Supervised Deep Learning" | Externo | noFollow |
| 10.1109/HPCC-CSS-ICESS.2015.45 | Externo | noFollow |
| 15411954 | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "ImageNet Classification with Deep Convolutional Neural Networks" | Externo | noFollow |
| Archived | Externo | noFollow |
| "Why do deep convolutional networks generalize so poorly to small image transformations?" | Externo | noFollow |
| 1533-7928 | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 2004.02806 | Externo | noFollow |
| 2022ITNNL..33.6999L | Externo | noFollow |
| 10.1109/TNNLS.2021.3084827 | Externo | noFollow |
| hdl | Interno | Passing Juice |
| 10072/405164 | Externo | noFollow |
| 34111009 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "CS231n Convolutional Neural Networks for Visual Recognition" | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "Pooling in convolutional neural networks for medical image analysis: a survey and an empirical study" | Externo | noFollow |
| 10.1007/s00521-022-06953-8 | Externo | noFollow |
| 1433-3058 | Externo | noFollow |
| 35125669 | Externo | noFollow |
| "Evaluation of Pooling Operations in Convolutional Architectures for Object Recognition" | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 1412.6071 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 1412.6806 | Externo | noFollow |
| cs.LG | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 2019ITVT...68.3224M | Externo | noFollow |
| 10.1109/tvt.2019.2899972 | Externo | noFollow |
| 0018-9545 | Externo | noFollow |
| 86674074 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "A Comparison of Pooling Methods for Convolutional Neural Networks" | Externo | noFollow |
| 2022ApSci..12.8643Z | Externo | noFollow |
| 2076-3417 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 2009.07485 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "A theory of steady-state activity in nerve-fiber networks: I. Definitions and preliminary lemmas" | Externo | noFollow |
| 10.1007/BF02478220 | Externo | noFollow |
| 0007-4985 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "Appropriate number and allocation of ReLUs in convolutional neural networks" | Externo | noFollow |
| ^ | Interno | Passing Juice |
| the original | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "Imagenet classification with deep convolutional neural networks" | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 2102.07757 | Externo | noFollow |
| 10.1109/ICASSP39728.2021.9414627 | Externo | noFollow |
| 231925012 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "Tracking Translation Invariance in CNNS" | Externo | noFollow |
| 2104.05997 | Externo | noFollow |
| 10.1007/978-3-030-66151-9_18 | Externo | noFollow |
| 233219976 | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 1106340711 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "Spatial Transformer Networks" | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 1106278545 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| Barner, Kenneth E. | Interno | Passing Juice |
| "Inductive conformal predictor for convolutional neural networks: Applications to active learning for image classification" | Externo | noFollow |
| 2019PatRe..90..172M | Externo | noFollow |
| 10.1016/j.patcog.2019.01.035 | Externo | noFollow |
| 0031-3203 | Externo | noFollow |
| 127253432 | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "Deep Learning With Conformal Prediction for Hierarchical Analysis of Large-Scale Whole-Slide Tissue Images" | Externo | noFollow |
| 2021IJBHI..25..371W | Externo | noFollow |
| 2168-2208 | Externo | noFollow |
| 32750907 | Externo | noFollow |
| 219885788 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "Dropout: A Simple Way to Prevent Neural Networks from overfitting" | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "Regularization of Neural Networks using DropConnect | ICML 2013 | JMLR W&CP" | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 1301.3557 | Externo | noFollow |
| "Best Practices for Convolutional Neural Networks Applied to Visual Document Analysis – Microsoft Research" | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 1207.0580 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "Dropout: A Simple Way to Prevent Neural Networks from Overfitting" | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 10.1016/s0364-0213(79)80008-7 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| ^ | Interno | Passing Juice |
| https://www.coursera.org/learn/neural-networks | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "The inside story of how AI got good enough to dominate Silicon Valley" | Externo | noFollow |
| Quartz | Interno | Passing Juice |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 10.1.1.92.5813 | Externo | noFollow |
| 10.1109/72.554195 | Externo | noFollow |
| 18255614 | Externo | noFollow |
| 2883848 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "A Convolutional Neural Network Approach for Objective Video Quality Assessment" | Externo | noFollow |
| 2006ITNN...17.1316L | Externo | noFollow |
| 10.1109/TNN.2006.879766 | Externo | noFollow |
| 17001990 | Externo | noFollow |
| 221185563 | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "ImageNet Large Scale Visual Recognition Competition 2014 (ILSVRC2014)" | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 1409.4842 | Externo | noFollow |
| 10.1109/CVPR.2015.7298594 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| Russakovsky, Olga | Interno | Passing Juice |
| Karpathy, Andrej | Interno | Passing Juice |
| 1409.0575 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "The Face Detection Algorithm Set To Revolutionize Image Search" | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 10.1.1.385.4740 | Externo | noFollow |
| 10.1007/978-3-642-25446-8_4 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 2013ITPAM..35..221J | Externo | noFollow |
| 10.1.1.169.4046 | Externo | noFollow |
| 10.1109/TPAMI.2012.59 | Externo | noFollow |
| 0162-8828 | Externo | noFollow |
| 22392705 | Externo | noFollow |
| 1923924 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 1801.10111 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| Large-scale video classification with convolutional neural networks | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 1406.2199 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "Segment-Tube: Spatio-Temporal Action Localization in Untrimmed Videos with Per-Frame Segmentation" | Externo | noFollow |
| 2018Senso..18.1657W | Externo | noFollow |
| 10.3390/s18051657 | Externo | noFollow |
| 1424-8220 | Externo | noFollow |
| 5982167 | Externo | noFollow |
| 29789447 | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 10.1109/icip.2018.8451692 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 10.1.1.294.5948 | Externo | noFollow |
| 10.1109/CVPR.2011.5995496 | Externo | noFollow |
| 6006618 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 1404.7296 | Externo | noFollow |
| cs.CL | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "Learning Semantic Representations Using Convolutional Neural Networks for Web Search – Microsoft Research" | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 1404.2188 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 1408.5882 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| A unified architecture for natural language processing: Deep neural networks with multitask learning | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 1103.0398 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 1702.01923 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 1803.01271 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 10.1007/S00521-021-06190-5 | Externo | noFollow |
| 236307579 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 2107.09355 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "DeepEthogram, a machine learning pipeline for supervised behavior classification from raw pixels" | Externo | noFollow |
| 10.7554/eLife.63377 | Externo | noFollow |
| 2050-084X | Externo | noFollow |
| 34473051 | Externo | noFollow |
| "Automated monitoring of honey bees with barcodes and artificial intelligence reveals two distinct social networks from a single affiliative behavior" | Externo | noFollow |
| 2023NatSR..13.1541G | Externo | noFollow |
| 10.1038/s41598-022-26825-4 | Externo | noFollow |
| 2045-2322 | Externo | noFollow |
| 36707534 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "Automatically identifying, counting, and describing wild animals in camera-trap images with deep learning" | Externo | noFollow |
| 2018PNAS..115E5716N | Externo | noFollow |
| 10.1073/pnas.1719367115 | Externo | noFollow |
| 0027-8424 | Externo | noFollow |
| 29871948 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| bioRxiv | Interno | Passing Juice |
| 10.1101/2025.04.08.647223 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 10.1101/2025.05.30.657023 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "DeepLabCut: markerless pose estimation of user-defined body parts with deep learning" | Externo | noFollow |
| 10.1038/s41593-018-0209-y | Externo | noFollow |
| 1097-6256 | Externo | noFollow |
| 30127430 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "DeepPoseKit, a software toolkit for fast and robust animal pose estimation using deep learning" | Externo | noFollow |
| 2019eLife...847994G | Externo | noFollow |
| 10.7554/eLife.47994 | Externo | noFollow |
| 31570119 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "Publisher Correction: SLEAP: A deep learning system for multi-animal pose tracking" | Externo | noFollow |
| 10.1038/s41592-022-01495-2 | Externo | noFollow |
| 1548-7091 | Externo | noFollow |
| 35468969 | Externo | noFollow |
| "DeepBehavior: A Deep Learning Toolbox for Automated Analysis of Animal and Human Behavior Imaging Data" | Externo | noFollow |
| 10.3389/fnsys.2019.00020 | Externo | noFollow |
| 1662-5137 | Externo | noFollow |
| 31133826 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 1906.03821 | Externo | noFollow |
| 10.1145/3292500.3330680 | Externo | noFollow |
| 182952311 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 1510.02855 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 1506.06579 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "Toronto startup has a faster way to discover effective medicines" | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "Startup Harnesses Supercomputers to Seek Cures" | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 1999ITNN...10.1382C | Externo | noFollow |
| 10.1109/72.809083 | Externo | noFollow |
| 18252639 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 2001ITEC....5..422C | Externo | noFollow |
| 10.1109/4235.942536 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| ^ | Interno | Passing Juice |
| 1412.3409 | Externo | noFollow |
| cs.AI | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 1412.6564 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "AlphaGo – Google DeepMind" | Externo | noFollow |
| the original | Externo | noFollow |
| ^ | Interno | Passing Juice |
| ^ | Interno | Passing Juice |
| ^ | Interno | Passing Juice |
| 1703.04691 | Externo | noFollow |
| stat.ML | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 1508.00317 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 1906.04397 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 10.21629/JSEE.2017.01.18 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 1908.07978 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| Hubert Mara | Interno | Passing Juice |
| 10.11588/data/IE8CCN | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 10.1109/ICDAR.2019.00032 | Externo | noFollow |
| 211026941 | Externo | noFollow |
| citation | Interno | Passing Juice |
| link | Interno | Passing Juice |
| ^ | Interno | Passing Juice |
| ^ | Interno | Passing Juice |
| YouTube | Interno | Passing Juice |
| ^ | Interno | Passing Juice |
| "CNN based common approach to handwritten character recognition of multiple scripts" | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "NIPS 2017" | Externo | noFollow |
| the original | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 1803.07179 | Externo | noFollow |
| 10.1007/978-3-319-92007-8_9 | Externo | noFollow |
| 1868-4238 | Externo | noFollow |
| 4058889 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "Action Recognition by an Attention-Aware Temporal Weighted Convolutional Neural Network" | Externo | noFollow |
| 2018Senso..18.1979W | Externo | noFollow |
| 10.3390/s18071979 | Externo | noFollow |
| 6069475 | Externo | noFollow |
| 29933555 | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 1508.04186v2 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 2015Natur.518..529M | Externo | noFollow |
| 10.1038/nature14236 | Externo | noFollow |
| 25719670 | Externo | noFollow |
| 205242740 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 2000ITSMB..30..403S | Externo | noFollow |
| 10.1.1.11.226 | Externo | noFollow |
| 10.1109/3477.846230 | Externo | noFollow |
| 1083-4419 | Externo | noFollow |
| 18252373 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "Convolutional Deep Belief Networks on CIFAR-10" | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 10.1.1.149.6800 | Externo | noFollow |
| 10.1145/1553374.1553453 | Externo | noFollow |
| 12008458 | Externo | noFollow |
| ^ | Interno | Passing Juice |
| 10.1007/b11963 | Externo | noFollow |
| 1304548 | Externo | noFollow |
| Archived | Externo | noFollow |
| ^ | Interno | Passing Juice |
| "Introduction to Machine Learning, Neural Networks, and Deep Learning" | Externo | noFollow |
| Archived | Externo | noFollow |
| CS231n: Convolutional Neural Networks for Visual Recognition | Externo | noFollow |
| Stanford | Interno | Passing Juice |
| vdumoulin/conv_arithmetic: A technical report on convolution arithmetic in the context of deep learning | Externo | noFollow |
| Artificial intelligence | Interno | Passing Juice |
| History | Interno | Passing Juice |
| timeline | Interno | Passing Juice |
| Companies | Interno | Passing Juice |
| Projects | Interno | Passing Juice |
| Parameter | Interno | Passing Juice |
| Double descent | Interno | Passing Juice |
| Gradient descent | Interno | Passing Juice |
| SGD | Interno | Passing Juice |
| Quasi-Newton method | Interno | Passing Juice |
| Conjugate gradient method | Interno | Passing Juice |
| Normalization | Interno | Passing Juice |
| Batchnorm | Interno | Passing Juice |
| Gating | Interno | Passing Juice |
| Weight initialization | Interno | Passing Juice |
| Datasets | Interno | Passing Juice |
| Prompt engineering | Interno | Passing Juice |
| Imitation | Interno | Passing Juice |
| Diffusion | Interno | Passing Juice |
| Latent diffusion model | Interno | Passing Juice |
| Autoregression | Interno | Passing Juice |
| Adversary | Interno | Passing Juice |
| RAG | Interno | Passing Juice |
| Uncanny valley | Interno | Passing Juice |
| Reflection | Interno | Passing Juice |
| Recursive self-improvement | Interno | Passing Juice |
| Hallucination | Interno | Passing Juice |
| Word embedding | Interno | Passing Juice |
| Vibe coding | Interno | Passing Juice |
| Safety | Interno | Passing Juice |
| Alignment | Interno | Passing Juice |
| Applications | Interno | Passing Juice |
| In-context learning | Interno | Passing Juice |
| Language model | Interno | Passing Juice |
| Large | Interno | Passing Juice |
| NMT | Interno | Passing Juice |
| Reasoning | Interno | Passing Juice |
| Model Context Protocol | Interno | Passing Juice |
| Intelligent agent | Interno | Passing Juice |
| Artificial human companion | Interno | Passing Juice |
| Humanity's Last Exam | Interno | Passing Juice |
| Lethal autonomous weapons (LAWs) | Interno | Passing Juice |
| Generative artificial intelligence (GenAI) | Interno | Passing Juice |
| Artificial general intelligence (AGI) | Interno | Passing Juice |
| Artificial superintelligence (ASI) | Interno | Passing Juice |
| WaveNet | Interno | Passing Juice |
| Human image synthesis | Interno | Passing Juice |
| HWR | Interno | Passing Juice |
| OCR | Interno | Passing Juice |
| Speech synthesis | Interno | Passing Juice |
| 15.ai | Interno | Passing Juice |
| ElevenLabs | Interno | Passing Juice |
| Speech recognition | Interno | Passing Juice |
| Whisper | Interno | Passing Juice |
| AlphaFold | Interno | Passing Juice |
| Text-to-image models | Interno | Passing Juice |
| Aurora | Interno | Passing Juice |
| DALL-E | Interno | Passing Juice |
| Firefly | Interno | Passing Juice |
| Flux | Interno | Passing Juice |
| GPT Image | Interno | Passing Juice |
| Ideogram | Interno | Passing Juice |
| Imagen | Interno | Passing Juice |
| Midjourney | Interno | Passing Juice |
| Recraft | Interno | Passing Juice |
| Stable Diffusion | Interno | Passing Juice |
| Dream Machine | Interno | Passing Juice |
| Runway Gen | Interno | Passing Juice |
| Hailuo AI | Interno | Passing Juice |
| Kling | Interno | Passing Juice |
| Sora | Interno | Passing Juice |
| Veo | Interno | Passing Juice |
| Music generation | Interno | Passing Juice |
| Riffusion | Interno | Passing Juice |
| Suno AI | Interno | Passing Juice |
| Udio | Interno | Passing Juice |
| Word2vec | Interno | Passing Juice |
| Seq2seq | Interno | Passing Juice |
| GloVe | Interno | Passing Juice |
| BERT | Interno | Passing Juice |
| T5 | Interno | Passing Juice |
| Llama | Interno | Passing Juice |
| Chinchilla AI | Interno | Passing Juice |
| PaLM | Interno | Passing Juice |
| GPT | Interno | Passing Juice |
| 1 | Interno | Passing Juice |
| 2 | Interno | Passing Juice |
| 3 | Interno | Passing Juice |
| J | Interno | Passing Juice |
| ChatGPT | Interno | Passing Juice |
| 4 | Interno | Passing Juice |
| 4o | Interno | Passing Juice |
| o1 | Interno | Passing Juice |
| o3 | Interno | Passing Juice |
| 4.5 | Interno | Passing Juice |
| 4.1 | Interno | Passing Juice |
| o4-mini | Interno | Passing Juice |
| 5 | Interno | Passing Juice |
| 5.1 | Interno | Passing Juice |
| 5.2 | Interno | Passing Juice |
| Claude | Interno | Passing Juice |
| Gemini | Interno | Passing Juice |
| Gemini (language model) | Interno | Passing Juice |
| Gemma | Interno | Passing Juice |
| Grok | Interno | Passing Juice |
| LaMDA | Interno | Passing Juice |
| BLOOM | Interno | Passing Juice |
| DBRX | Interno | Passing Juice |
| Project Debater | Interno | Passing Juice |
| IBM Watson | Interno | Passing Juice |
| IBM Watsonx | Interno | Passing Juice |
| Granite | Interno | Passing Juice |
| PanGu-Σ | Interno | Passing Juice |
| DeepSeek | Interno | Passing Juice |
| Qwen | Interno | Passing Juice |
| AlphaZero | Interno | Passing Juice |
| OpenAI Five | Interno | Passing Juice |
| MuZero | Interno | Passing Juice |
| Action selection | Interno | Passing Juice |
| AutoGPT | Interno | Passing Juice |
| Robot control | Interno | Passing Juice |
| Alan Turing | Interno | Passing Juice |
| Warren Sturgis McCulloch | Interno | Passing Juice |
| Walter Pitts | Interno | Passing Juice |
| John von Neumann | Interno | Passing Juice |
| Christopher D. Manning | Interno | Passing Juice |
| Claude Shannon | Interno | Passing Juice |
| Shun'ichi Amari | Interno | Passing Juice |
| Takeo Kanade | Interno | Passing Juice |
| Marvin Minsky | Interno | Passing Juice |
| John McCarthy | Interno | Passing Juice |
| Nathaniel Rochester | Interno | Passing Juice |
| Allen Newell | Interno | Passing Juice |
| Cliff Shaw | Interno | Passing Juice |
| Herbert A. Simon | Interno | Passing Juice |
| Oliver Selfridge | Interno | Passing Juice |
| Frank Rosenblatt | Interno | Passing Juice |
| Bernard Widrow | Interno | Passing Juice |
| Joseph Weizenbaum | Interno | Passing Juice |
| Seymour Papert | Interno | Passing Juice |
| Seppo Linnainmaa | Interno | Passing Juice |
| Paul Werbos | Interno | Passing Juice |
| Geoffrey Hinton | Interno | Passing Juice |
| John Hopfield | Interno | Passing Juice |
| Jürgen Schmidhuber | Interno | Passing Juice |
| Lotfi A. Zadeh | Interno | Passing Juice |
| Stephen Grossberg | Interno | Passing Juice |
| Alex Graves | Interno | Passing Juice |
| James Goodnight | Interno | Passing Juice |
| Andrew Ng | Interno | Passing Juice |
| Fei-Fei Li | Interno | Passing Juice |
| Ilya Sutskever | Interno | Passing Juice |
| Oriol Vinyals | Interno | Passing Juice |
| Quoc V. Le | Interno | Passing Juice |
| Ian Goodfellow | Interno | Passing Juice |
| Demis Hassabis | Interno | Passing Juice |
| David Silver | Interno | Passing Juice |
| Ashish Vaswani | Interno | Passing Juice |
| Noam Shazeer | Interno | Passing Juice |
| Aidan Gomez | Interno | Passing Juice |
| John Schulman | Interno | Passing Juice |
| Mustafa Suleyman | Interno | Passing Juice |
| Jan Leike | Interno | Passing Juice |
| Daniel Kokotajlo | Interno | Passing Juice |
| François Chollet | Interno | Passing Juice |
| Neural Turing machine | Interno | Passing Juice |
| Differentiable neural computer | Interno | Passing Juice |
| Residual neural network (RNN) | Interno | Passing Juice |
| Highway network | Interno | Passing Juice |
| Variational autoencoder (VAE) | Interno | Passing Juice |
| Graph neural network (GNN) | Interno | Passing Juice |
| Regulation of artificial intelligence | Interno | Passing Juice |
| Ethics of artificial intelligence | Interno | Passing Juice |
| Precautionary principle | Interno | Passing Juice |
| Artificial Intelligence Act (AI Act) | Interno | Passing Juice |
| AI bubble | Interno | Passing Juice |
| AI literacy | Interno | Passing Juice |
| AI winter | Interno | Passing Juice |
| In education | Interno | Passing Juice |
| In architecture | Interno | Passing Juice |
| In visual art | Interno | Passing Juice |
| Category | Interno | Passing Juice |
| Authority control databases | Interno | Passing Juice |
| Latvia | Externo | noFollow |
| https://en.wikipedia.org/w/index.php?title=Convolutional_neural_network&oldid=1335778735 | Externo | Passing Juice |
| Categories | Interno | Passing Juice |
| Neural network architectures | Interno | Passing Juice |
| Computer vision | Interno | Passing Juice |
| Computational neuroscience | Interno | Passing Juice |
| Webarchive template wayback links | Interno | Passing Juice |
| All articles with dead external links | Interno | Passing Juice |
| Articles with dead external links from July 2022 | Interno | Passing Juice |
| CS1 German-language sources (de) | Interno | Passing Juice |
| Articles with short description | Interno | Passing Juice |
| Short description is different from Wikidata | Interno | Passing Juice |
| All articles with unsourced statements | Interno | Passing Juice |
| Articles with unsourced statements from October 2017 | Interno | Passing Juice |
| All articles needing examples | Interno | Passing Juice |
| Articles needing examples from October 2017 | Interno | Passing Juice |
| Articles with unsourced statements from March 2024 | Interno | Passing Juice |
| All articles with specifically marked weasel-worded phrases | Interno | Passing Juice |
| Articles with specifically marked weasel-worded phrases from December 2018 | Interno | Passing Juice |
| Articles needing additional references from June 2017 | Interno | Passing Juice |
| All articles needing additional references | Interno | Passing Juice |
| Wikipedia articles needing clarification from December 2018 | Interno | Passing Juice |
| Articles with unsourced statements from June 2019 | Interno | Passing Juice |
| Creative Commons Attribution-ShareAlike 4.0 License | Interno | Passing Juice |
| Terms of Use | Externo | Passing Juice |
| Privacy Policy | Externo | Passing Juice |
| Wikimedia Foundation, Inc. | Externo | noFollow |
| About Wikipedia | Interno | Passing Juice |
| Disclaimers | Interno | Passing Juice |
| Contact Wikipedia | Interno | Passing Juice |
| Legal & safety contacts | Externo | Passing Juice |
| Code of Conduct | Externo | Passing Juice |
| Developers | Externo | Passing Juice |
| Statistics | Externo | Passing Juice |
| Cookie statement | Externo | Passing Juice |
| Mobile view | Interno | Passing Juice |
SEO Keywords
Keywords Cloud
Consistenza Keywords
| Keyword | Contenuto | Title | Keywords | Description | Headings |
|---|
Usabilita
Url
Dominio : cnn.ai
Lunghezza : 6
Favicon
Grande, il tuo sito usa una favicon.
Stampabilita
Non abbiamo riscontrato codice CSS Print-Friendly.
Lingua
Buono. La tua lingua dichiarata en.
Dublin Core
Questa pagina non sfrutta i vantaggi di Dublin Core.
Documento
Doctype
HTML 5
Encoding
Perfetto. Hai dichiarato che il tuo charset e UTF-8.
Validita W3C
Errori : 0
Avvisi : 0
Email Privacy
Grande. Nessun indirizzo mail e stato trovato in plain text!
Deprecated HTML
| Deprecated tags | Occorrenze |
|---|---|
| <u> | 2 |
Tags HTML deprecati sono tags HTML che non vengono piu utilizzati. Ti raccomandiamo di rimuoverli o sostituire questi tags HTML perche ora sono obsoleti.
Suggerimenti per velocizzare
 |
Attenzione! Cerca di evitare di utilizzare nested tables in HTML. |
|
Molto male, il tuo sito web utilizza stili CSS inline. |
 |
Grande, il tuo sito web ha pochi file CSS. |
|
Perfetto, il tuo sito web ha pochi file JavaScript. |
|
Peccato, il vostro sito non approfitta di gzip. |
Mobile
Mobile Optimization
|
Apple Icon |
|
Meta Viewport Tag |
|
Flash content |
Ottimizzazione
XML Sitemap
Non trovato
Il tuo sito web non ha una sitemap XML - questo può essere problematico.
A elenca sitemap URL che sono disponibili per la scansione e possono includere informazioni aggiuntive come gli ultimi aggiornamenti del tuo sito, frequenza delle variazioni e l'importanza degli URL. In questo modo i motori di ricerca di eseguire la scansione del sito in modo più intelligente.
Robots.txt
https://cnn.ai/robots.txt
Grande, il vostro sito ha un file robots.txt.
Analytics
Non trovato
Non abbiamo rilevato uno strumento di analisi installato su questo sito web.
Web analytics consentono di misurare l'attività dei visitatori sul tuo sito web. Si dovrebbe avere installato almeno un strumento di analisi, ma può anche essere buona per installare una seconda, al fine di un controllo incrociato dei dati.
PageSpeed Insights
Dispositivo
Categorie
Free SEO Testing Tool
Free SEO Testing Tool e uno strumento di ottimizzazione per i motori di ricerca (seo tool) che serve per analizzare le tue pagine web