How do you do multi-class classification with a CNN network?
17 views (last 30 days)
Show older comments
Michael Bilenko
on 17 Apr 2021
Commented: Mahesh Taparia
on 24 Apr 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 Comments
Accepted Answer
Mahesh Taparia
on 19 Apr 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!
More Answers (0)
See Also
Categories
Find more on Recognition, Object Detection, and Semantic Segmentation in Help Center and File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!