How to start the training of a deep net from a given state?

1 次查看(过去 30 天)
I would like to start the training of a deep net from the state it was in after a previous training. In my application the user iteratively adds annotations and I want to avoid training the netwrok from scratch at each iteration. Here is the code I use to define and train the network:
layers = [ ... imageInputLayer([2*BoxRad+1 2*BoxRad+1 1]) convolution2dLayer([9 9],100,'Stride',1) reluLayer maxPooling2dLayer(2,'Stride',2) convolution2dLayer([5 5],25,'Stride',1) reluLayer maxPooling2dLayer(2,'Stride',2) fullyConnectedLayer(2) softmaxLayer classificationLayer]; options = trainingOptions('sgdm', 'MaxEpochs', 30, 'MiniBatchSize', 32); net = trainNetwork(Images,Lbl,layers,options);

回答(0 个)

类别

Help CenterFile Exchange 中查找有关 Sequence and Numeric Feature Data Workflows 的更多信息

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by