How to train features that have been extracted by using GoogleNet?
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Hello,
I extracted features by using GoogleNet, but I do not know how to train it to create classifier?
Thanks in advance
6 Comments
rcjr15
on 8 Nov 2017
How did you extracted the features using Googlenet. Kindly help.
sahar alhaddad
on 10 Nov 2017
rcjr15
on 13 Nov 2017
I am getting error while using the above command. Can someone help me with this? @Jatin Waghela @Mathworks
sahar alhaddad
on 15 Nov 2017
rcjr15
on 19 Nov 2017
Yes. I have defined trainingSet.
sahar alhaddad
on 20 Nov 2017
Answers (2)
Jatin Waghela
on 3 Oct 2017
0 votes
If I understood you correctly, you would like to transfer learning to retrain GoogLeNet to create a classifier.
Please refer to the below documentation link which gives more information on Pretrained GoogLeNet convolutional neural network:
7 Comments
sahar alhaddad
on 3 Oct 2017
keke zhang
on 7 Nov 2017
Hi,I want to know how to extract features from GoogLeNet, the function 'activations' are not work, the object function of DAGNetwork only has three functions, and there not exist the function 'activations'.https://cn.mathworks.com/help/nnet/ref/dagnetwork.html?s_tid=srchtitle
rcjr15
on 8 Nov 2017
Yes, the activations function is not working and how to extract the features learned by the googlenet ? In Alexnet we could use activation (Alexnet,trainimages,'fc7') in order to extract the features. Any similar function for googlenet?
sahar alhaddad
on 10 Nov 2017
rcjr15
on 13 Nov 2017
I am getting error while using the above command. Can someone help me with this? @Jatin Waghela
Sivaramakrishnan Rajaraman
on 28 Nov 2017
Has anyone tried to extract features from layers other than pool5-drop_7*7_s1? If so what is the syntax?
umit kacar
on 7 Mar 2018
https://www.mathworks.com/matlabcentral/answers/379635-error-using-activations-with-googlenet-in-r2017b#answer_302390
michael scheinfeild
on 22 Jul 2018
use some layer as the feature . then you can use it for other classifier
net = googlenet;
inputSize = net.Layers(1).InputSize;
imds = imageDatastore(dbpathSave)
augimdsTrain = augmentedImageDatastore(inputSize(1:2),imds );
%%Extract Image Features
layer = 'loss3-classifier';%1000
featuresTrain = activations(net,augimdsTrain,layer,'OutputAs','rows');
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