How to train features that have been extracted by using GoogleNet?
이전 댓글 표시
Hello,
I extracted features by using GoogleNet, but I do not know how to train it to create classifier?
Thanks in advance
댓글 수: 6
rcjr15
2017년 11월 8일
How did you extracted the features using Googlenet. Kindly help.
sahar alhaddad
2017년 11월 10일
rcjr15
2017년 11월 13일
I am getting error while using the above command. Can someone help me with this? @Jatin Waghela @Mathworks
sahar alhaddad
2017년 11월 15일
rcjr15
2017년 11월 19일
Yes. I have defined trainingSet.
sahar alhaddad
2017년 11월 20일
답변 (2개)
Jatin Waghela
2017년 10월 3일
0 개 추천
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:
댓글 수: 7
sahar alhaddad
2017년 10월 3일
keke zhang
2017년 11월 7일
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
2017년 11월 8일
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
2017년 11월 10일
rcjr15
2017년 11월 13일
I am getting error while using the above command. Can someone help me with this? @Jatin Waghela
Sivaramakrishnan Rajaraman
2017년 11월 28일
Has anyone tried to extract features from layers other than pool5-drop_7*7_s1? If so what is the syntax?
umit kacar
2018년 3월 7일
https://www.mathworks.com/matlabcentral/answers/379635-error-using-activations-with-googlenet-in-r2017b#answer_302390
michael scheinfeild
2018년 7월 22일
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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