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Convolutional neural network - Wikipedia

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Convolutional neural network - Wikipedia

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title Convolutional neural network - Wikipedia
type website

Rubriker

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

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