Uses of Class
org.neuroph.nnet.comp.layer.FeatureMapsLayer

Packages that use FeatureMapsLayer

Package	Description
org.neuroph.nnet.comp	Provides components for the specific neural network models.
org.neuroph.nnet.comp.layer	Provides various specific layer types

Uses of FeatureMapsLayer in org.neuroph.nnet.comp

Methods in org.neuroph.nnet.comp with parameters of type FeatureMapsLayer

Modifier and Type	Method and Description
static void	ConvolutionalUtils.connectFeatureMaps(FeatureMapsLayer fromLayer, FeatureMapsLayer toLayer, int fromFeatureMapIndex, int toFeatureMapIndex) Creates connections between two feature maps - not used???
static void	ConvolutionalUtils.fullConnectMapLayers(FeatureMapsLayer fromLayer, FeatureMapsLayer toLayer) Creates full connectivity between feature maps in two layers

Uses of FeatureMapsLayer in org.neuroph.nnet.comp.layer

Subclasses of FeatureMapsLayer in org.neuroph.nnet.comp.layer

Modifier and Type	Class and Description
class	ConvolutionalLayer Convolutional layer is a special type of layer, used in convolutional neural networks.
class	InputMapsLayer Input layer for convolutional networks
class	PoolingLayer Pooling layer is a special type of feature maps layer (FeatureMapsLayer) which is used in convolutional networks.

Constructors in org.neuroph.nnet.comp.layer with parameters of type FeatureMapsLayer

Constructor and Description
ConvolutionalLayer(FeatureMapsLayer fromLayer, Dimension2D kernelDimension, int numberOfMaps) Creates convolutional layer with specified kernel, appropriate map dimensions in regard to previous layer (fromLayer param) and specified number of feature maps with default neuron settings for convolutional layer.
ConvolutionalLayer(FeatureMapsLayer fromLayer, Dimension2D kernelDimension, int numberOfMaps, Class<? extends TransferFunction> transferFunction) Creates convolutional layer with specified kernel, appropriate map dimensions in regard to previous layer (fromLayer param) and specified number of feature maps with default neuron settings for convolutional layer.
ConvolutionalLayer(FeatureMapsLayer fromLayer, Dimension2D kernelDimension, int numberOfMaps, NeuronProperties neuronProp) Creates convolutional layer with specified kernel, appropriate map dimensions in regard to previous layer (fromLayer param) and specified number of feature maps with given neuron properties.
PoolingLayer(FeatureMapsLayer fromLayer, Dimension2D kernelDim) Creates pooling layer with specified kernel, appropriate map dimensions in regard to previous layer (fromLayer param) and specified number of feature maps with default neuron settings for pooling layer.
PoolingLayer(FeatureMapsLayer fromLayer, Dimension2D kernelDim, int numberOfMaps, NeuronProperties neuronProp) Creates pooling layer with specified kernel, appropriate map dimensions in regard to previous layer (fromLayer param) and specified number of feature maps with given neuron properties.