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How do you do multi-class classification with a CNN network?

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Michael Bilenko
Michael Bilenko 2021 年 4 月 17 日
コメント済み: Mahesh Taparia 2021 年 4 月 24 日
Currently I have a CNN network with a the classification layer.
net = alexnet;
layersTransfer = net.Layers(1:end-3);
numClasses = 5;
layers = [
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?


Mahesh Taparia
Mahesh Taparia 2021 年 4 月 19 日
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!
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