ConvolutionalLayer Class Reference

ConfolutionLayer class. More...

#include <SimdNeural.hpp>

Inheritance diagram for ConvolutionalLayer:

Public Member Functions
	ConvolutionalLayer (Function::Type f, const Size &srcSize, size_t srcDepth, size_t dstDepth, const Size &coreSize, bool valid=true, bool bias=true, const View &connection=View())
	Creates new ConfolutionLayer class. More...
Public Member Functions inherited from Layer
virtual	~Layer ()

Additional Inherited Members
Public Types inherited from Layer
enum	Type {   Input ,   Convolutional ,   MaxPooling ,   AveragePooling ,   FullyConnected ,   Dropout }
enum	Method {   Fast ,   Check ,   Train }

Detailed Description

ConfolutionLayer class.

Convolutional layer in neural network.

Constructor & Destructor Documentation

ConvolutionalLayer()

ConvolutionalLayer	(	Function::Type	f,
		const Size &	srcSize,
		size_t	srcDepth,
		size_t	dstDepth,
		const Size &	coreSize,
		bool	valid = true,
		bool	bias = true,
		const View &	connection = View()
	)

Creates new ConfolutionLayer class.

Parameters

[in]	f	- a type of activation function used in this layer.
[in]	srcSize	- a size (width and height) of input image.
[in]	srcDepth	- a number of input channels (images).
[in]	dstDepth	- a number of output channels (images).
[in]	coreSize	- a size of convolution core.
[in]	valid	- a boolean flag (True - only original image points are used in convolution, so output image is decreased; False - input image is padded by zeros and output image has the same size). By default its true.
[in]	bias	- a boolean flag (enabling of bias). By default its True.
[in]	connection	- a table of connections between input and output channels. By default all channels are connected.