mlpack 3.4.2
Public Member Functions | List of all members
DiceLoss< InputDataType, OutputDataType > Class Template Reference

The dice loss performance function measures the network's performance according to the dice coefficient between the input and target distributions. More...

#include <dice_loss.hpp>

Public Member Functions

 DiceLoss (const double smooth=1)
 Create the DiceLoss object. More...
 
template<typename InputType , typename TargetType , typename OutputType >
void Backward (const InputType &input, const TargetType &target, OutputType &output)
 Ordinary feed backward pass of a neural network. More...
 
template<typename InputType , typename TargetType >
InputType::elem_type Forward (const InputType &input, const TargetType &target)
 Computes the dice loss function. More...
 
OutputDataType & OutputParameter ()
 Modify the output parameter. More...
 
OutputDataType & OutputParameter () const
 Get the output parameter. More...
 
template<typename Archive >
void serialize (Archive &ar, const unsigned int)
 Serialize the layer. More...
 
double & Smooth ()
 Modify the smooth. More...
 
double Smooth () const
 Get the smooth. More...
 

Detailed Description

template<typename InputDataType = arma::mat, typename OutputDataType = arma::mat>
class mlpack::ann::DiceLoss< InputDataType, OutputDataType >

The dice loss performance function measures the network's performance according to the dice coefficient between the input and target distributions.

For more information see the following.

@article{Milletari2016,
author = {Fausto Milletari and Nassir Navab and Seyed{-}Ahmad Ahmadi},
title = {V-Net: Fully Convolutional Neural Networks for
Volumetric Medical Image Segmentation},
journal = {CoRR},
volume = {abs/1606.04797},
year = {2016},
url = {http://arxiv.org/abs/1606.04797},
archivePrefix = {arXiv},
eprint = {1606.04797},
}
Template Parameters
InputDataTypeType of the input data (arma::colvec, arma::mat, arma::sp_mat or arma::cube).
OutputDataTypeType of the output data (arma::colvec, arma::mat, arma::sp_mat or arma::cube).

Definition at line 50 of file dice_loss.hpp.

Constructor & Destructor Documentation

◆ DiceLoss()

DiceLoss ( const double  smooth = 1)

Create the DiceLoss object.

Parameters
smoothThe Laplace smoothing parameter.

Member Function Documentation

◆ Backward()

void Backward ( const InputType &  input,
const TargetType &  target,
OutputType &  output 
)

Ordinary feed backward pass of a neural network.

Parameters
inputThe propagated input activation.
targetThe target vector.
outputThe calculated error.

◆ Forward()

InputType::elem_type Forward ( const InputType &  input,
const TargetType &  target 
)

Computes the dice loss function.

Parameters
inputInput data used for evaluating the specified function.
targetThe target vector.

◆ OutputParameter() [1/2]

OutputDataType & OutputParameter ( )
inline

Modify the output parameter.

Definition at line 85 of file dice_loss.hpp.

◆ OutputParameter() [2/2]

OutputDataType & OutputParameter ( ) const
inline

Get the output parameter.

Definition at line 83 of file dice_loss.hpp.

◆ serialize()

void serialize ( Archive &  ar,
const unsigned int   
)

Serialize the layer.

◆ Smooth() [1/2]

double & Smooth ( )
inline

Modify the smooth.

Definition at line 90 of file dice_loss.hpp.

◆ Smooth() [2/2]

double Smooth ( ) const
inline

Get the smooth.

Definition at line 88 of file dice_loss.hpp.


The documentation for this class was generated from the following file: