Uses of Class
org.neuroph.nnet.comp.Dimension2D

Packages that use Dimension2D

Package	Description
org.neuroph.nnet	Provides out-of-the-box neural networks
org.neuroph.nnet.comp	Provides components for the specific neural network models.
org.neuroph.nnet.comp.layer	Provides various specific layer types

Uses of Dimension2D in org.neuroph.nnet

Methods in org.neuroph.nnet with parameters of type Dimension2D

Modifier and Type	Method and Description
ConvolutionalNetwork.Builder	ConvolutionalNetwork.Builder.withConvolutionLayer(Dimension2D kernelDimension, int numberOfMaps, Class<? extends TransferFunction> transferFunction)

Uses of Dimension2D in org.neuroph.nnet.comp

Constructors in org.neuroph.nnet.comp with parameters of type Dimension2D

Constructor and Description
Kernel(Dimension2D dimension) Creates new kernel with specified width and height

Uses of Dimension2D in org.neuroph.nnet.comp.layer

Fields in org.neuroph.nnet.comp.layer declared as Dimension2D

Modifier and Type	Field and Description
protected Dimension2D	FeatureMapsLayer.mapDimensions Dimensions for all 2D layers (feature maps)

Methods in org.neuroph.nnet.comp.layer that return Dimension2D

Modifier and Type	Method and Description
Dimension2D	FeatureMapLayer.getDimensions() Returns dimensions of this layer
Dimension2D	FeatureMapsLayer.getMapDimensions() Returns dimensions of feature maps in this layer

Methods in org.neuroph.nnet.comp.layer with parameters of type Dimension2D

Modifier and Type	Method and Description
protected void	FeatureMapsLayer.createFeatureMaps(int mapCount, Dimension2D mapDimensions, Dimension2D kernelDimension, NeuronProperties neuronProperties) Creates and adds specified number of feature maps to this layer

Constructors in org.neuroph.nnet.comp.layer with parameters of type Dimension2D

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.
FeatureMapLayer(Dimension2D dimensions, Dimension2D kernelDimension) Creates an empty 2D layer with specified dimensions and kernel
FeatureMapLayer(Dimension2D dimensions, NeuronProperties neuronProperties) Creates an empty 2D layer with specified dimensions
FeatureMapLayer(Dimension2D dimensions, NeuronProperties neuronProperties, Dimension2D kernelDimension) Creates 2D layer with specified dimensions, filled with neurons with specified properties
FeatureMapsLayer(Dimension2D mapDimensions) Creates a new empty feature maps layer with specified kernel and feature map dimensions.
FeatureMapsLayer(Dimension2D kernelDimension, Dimension2D mapDimensions, int mapCount, NeuronProperties neuronProp) Creates new feature maps layer with specified kernel and feature maps.
FeatureMapsLayer(Dimension2D mapDimensions, int mapCount, NeuronProperties neuronProp)
InputMapsLayer(Dimension2D mapDimensions, int mapCount) Create InputMapsLayer with specified number of maps with specified dimensions
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.