Convolutional Neural Networks for Matlab for classification and segmentation, including Invariang Backpropagation (IBP) and Adversarial Training (AT) algorithms. Trained on GPU, require cuDNN v5.
Hi.
I'm using the ConvNet library with Matlab on medical images (2 classes: positive or negative). In the training phase I obtained the same good results that I have obtained previously with the DeepLearnToolbox but when I test the net on new images loading the weights saved during training something wrong happen: the images are classified all positive or all negative. With the DeepLearnToolbox instead, using the same test images, I have some images classified positive and some negative. What can I do?
Hi. I'm using the ConvNet library with Matlab on medical images (2 classes: positive or negative). In the training phase I obtained the same good results that I have obtained previously with the DeepLearnToolbox but when I test the net on new images loading the weights saved during training something wrong happen: the images are classified all positive or all negative. With the DeepLearnToolbox instead, using the same test images, I have some images classified positive and some negative. What can I do?