Deep Convolutional Neural Networks for Hyperspectral Image Classification

Algorithm 1

Our CNN-based method.

  Constructing the CNN Model

function INITCNNMODEL (, [])

 layerType = convolution, max-pooling, fully-connected, fully-connected;

 layerActivation = , , ,

 model = new Model();

 for   to   do

  layer = new Layer();

  layer.type = layerType;

  layer.inputSize =

  layer.neurons = new Neuron ;

  layer.params = ;

  model.addLayer(layer);

 end for

 return model;

end function

  Training the CNN Model

Initialize learning rate , number of max iteration , min error , training

batchs , bach size , and so on;

Compute , , , , , according to and ;

Generate random weights of the CNN;

cnnModel = InitCNNModel(, []);

iter = 0; err = +;

while err and iter   do

 err = ;

 for bach to   do

   = cnnModel.train (TrainingDatas, TrainingLabels), as (4) and (8);

  Update using (7);

  err = err + mean();

 end for

 err = err/;

 iter++;

end while

Save parameters of the CNN;