Caffe-DeepBinaryCode
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kevinlin311tw
Porting to Tensorflow / Keras. Help Needed
Hello
I am trying to reproduce the results of this paper using Keras. I have implemented the loss function as seen in the paper, but the accuracy of the classifier never goes above 10%.
To test the loss implementation, I am using a tiny CNN trained from scratch. The model structure is as seen in the image attached. I have also tried building on top of a pre-trained VGG16, but the results are the same.
As seen from the name, the second last layer called "latent_48bit" is the latent layer with the sigmoid activation. The final layer is the softmax classifier.
Is the model architecture correct?
Also, can you help me with the loss function? I believe that's where I am going wrong.
How about removing your loss function, and training with only the softmax loss function at first?
2017-07-19 23:25 GMT-07:00 Sarthak Yadav [email protected]:
Hello
I am trying to reproduce the results of this paper using Keras. I have implemented the loss function as seen in the paper, but the accuracy of the classifier never goes above 10%. To test the loss implementation, I am using a tiny CNN trained from scratch. The model structure is as seen in the image attached. I have also tried building on top of a pre-trained VGG16, but the results are the same. [image: model] https://user-images.githubusercontent.com/8536280/28368776-39529454-6cb3-11e7-9c5a-52c4c3f3b9aa.png As seen from the name, the second last layer called "latent_48bit" is the latent layer with the sigmoid activation. The final layer is the softmax classifier.
Is the model architecture correct?
Also, can you help me with the loss function? I believe that's where I am going wrong.
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Best regards,
林可昀
Kevin Lin
