How do you do multi-class classification with a CNN network?
10 vues (au cours des 30 derniers jours)
Afficher commentaires plus anciens
Michael Bilenko
le 17 Avr 2021
Commenté : Mahesh Taparia
le 24 Avr 2021
Currently I have a CNN network with a the classification layer.
net = alexnet;
layersTransfer = net.Layers(1:end-3);
numClasses = 5;
layers = [
layersTransfer
fullyConnectedLayer(numClasses,'Name', 'fc','WeightLearnRateFactor',1,'BiasLearnRateFactor',1)
softmaxLayer('Name', 'softmax')
classificationLayer('Name', 'classOutput')];
There are 5 different classes and each image can have multiple classes. However I can not find a way to train a network where each image has more than one possible class. How can I change my network so I can train it with data where there are multiple labels?
0 commentaires
Réponse acceptée
Mahesh Taparia
le 19 Avr 2021
Hi
As per your problem, I am assuming you are having multiple categorical objects in a single image. So the problem is no longer an image classification, it is an object detection problem. You can refer to the documentation of object detection, here are some useful links:
Hope it will help!
Plus de réponses (0)
Voir également
Catégories
En savoir plus sur Recognition, Object Detection, and Semantic Segmentation 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!