Module ITKNeuralNetworks

Collaboration diagram for Module ITKNeuralNetworks:

Classes
class	itk::Statistics::BackPropagationLayer< TMeasurementVector, TTargetVector >
class	itk::Statistics::BatchSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >
class	itk::Statistics::CompletelyConnectedWeightSet< TMeasurementVector, TTargetVector >
class	itk::Statistics::ErrorBackPropagationLearningFunctionBase< LayerType, TTargetVector >
class	itk::Statistics::ErrorBackPropagationLearningWithMomentum< LayerType, TTargetVector >
class	itk::Statistics::ErrorFunctionBase< TMeasurementVector, TTargetVector >
class	itk::Statistics::GaussianRadialBasisFunction< ScalarType >
class	itk::Statistics::GaussianTransferFunction< ScalarType >
class	itk::Statistics::HardLimitTransferFunction< ScalarType >
class	itk::Statistics::IdentityTransferFunction< ScalarType >
class	itk::Statistics::InputFunctionBase< TMeasurementVector, TTargetVector >
class	itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >
class	itk::Statistics::LayerBase< TMeasurementVector, TTargetVector >
class	itk::Statistics::LearningFunctionBase< LayerType, TTargetVector >
class	itk::Statistics::LogSigmoidTransferFunction< ScalarType >
class	MeanSquaredErrorFunction_
class	itk::Statistics::MultilayerNeuralNetworkBase< TMeasurementVector, TTargetVector, TLearningLayer >
class	itk::Statistics::MultiquadricRadialBasisFunction< ScalarType >
class	itk::Statistics::NeuralNetworkObject< TMeasurementVector, TTargetVector >
class	itk::Statistics::NNetDistanceMetricBase< TMeasurementVector >
class	itk::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector >
class	itk::Statistics::ProductInputFunction< TMeasurementVector, ScalarType >
class	itk::Statistics::QuickPropLearningRule< LayerType, TTargetVector >
class	itk::Statistics::RadialBasisFunctionBase< ScalarType >
class	itk::Statistics::RBFBackPropagationLearningFunction< LayerType, TTargetVector >
class	itk::Statistics::RBFLayer< TMeasurementVector, TTargetVector >
class	itk::Statistics::RBFNetwork< TMeasurementVector, TTargetVector >
class	itk::Statistics::SigmoidTransferFunction< ScalarType >
class	itk::Statistics::SignedHardLimitTransferFunction< ScalarType >
class	itk::Statistics::SquaredDifferenceErrorFunction< TMeasurementVector, ScalarType >
class	itk::Statistics::SumInputFunction< TMeasurementVector, ScalarType >
class	itk::Statistics::SymmetricSigmoidTransferFunction< ScalarType >
class	itk::Statistics::TanHTransferFunction< ScalarType >
class	itk::Statistics::TanSigmoidTransferFunction< ScalarType >
class	itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >
class	itk::Statistics::TransferFunctionBase< ScalarType >
class	itk::Statistics::TwoHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector >
class	itk::Statistics::WeightSetBase< TMeasurementVector, TTargetVector >

Detailed Description

This module contains classes and support classes for the calculation of artificial neural networks. This can be used, for instance, for image classification.

Dependencies:

• Module ITKStatistics