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.
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.