how to copy layers and connections from an existing neural network?
17 vues (au cours des 30 derniers jours)
Afficher commentaires plus anciens
just installed the latest version and find the support for deep learning is better and better. here, i have a question. I want to create a new network, but i do not want to write from scratch. take googlenet for example, I want to create a new network which can be a little like googlenet. but not all the same. maybe I need to refer some layers or structure. so how to copy layers and connections from an existing neural network?
0 commentaires
Réponses (1)
Von Duesenberg
le 11 Juil 2018
Something along the lines (I had an exemple withe Alexnet, but the basic principle should be identical; here, I just resize the input layers because I have gray, not RGB, images, and I have 45 classes):
net = alexnet;
layers = net.Layers;
layers(1) = imageInputLayer([227, 227,1]);
layers(2) = convolution2dLayer([11, 11], 96,'Padding',0, 'Stride', 4, 'BiasLearnRateFactor',2);
layers(23) = fullyConnectedLayer(45);
layers(24) = softmaxLayer();
layers(25) = classificationLayer();
1 commentaire
Voir également
Catégories
En savoir plus sur Image Data Workflows dans Help Center et File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!