Tag: conv-neural-network

Data type preference for training CNN?

I originally was using input data of int8 type ranging from 0-255 before learning that standardizing and normalizing should increase learning speeds and accuracy. I attempted both, with and without a mean of zero, and none of these methods improved learning speed or accuracy for my model relative to 0-255, int8 approach. I’m just wondering whether training with, for example,

Extracting Transfer learning output from CNN Keras

How to take the intermediate Transfer learning output. ? Eg: Tried: Answer There’s an unresolved issue in Tensorflow on this problem. According to the issue, you need to pass inputs of both outer model and inner model to get the output of inner model.

Problem with data cast on the GPU in PyTorch

Im trying to do an image classifier, but im having a problem with the data cast on the GPU. Model already is in cuda, but i get error that says Whats the problem with input.to(args[‘device’])? Answer UPDATE: According to the OP, an aditional data.to(device) before the train loop caused this issue. you are probably getting a string like 0 or

RuntimeError: Given groups=1, weight of size [32, 16, 5, 5], expected input[16, 3, 448, 448] to have 16 channels, but got 3 channels instead

I am getting the following error and can’t figure out why. I printed the input size of my torch before it gets fed to the CNN: Here is my error message: I defined a CNN with 5 convolutional layers and two fully connected layers. I am feeding in batches of 16 and have resized the images to be (448×448). The

How to add a traditional classifier(SVM) to my CNN model

here’s my model i want to make svm classifier as my final classifier in this model so how can i do that? also another question i want to know the predicted class of a certain input so when i use it only gives me probabilities so how can i solve that too Answer You can use neural network as feature

Giving output of one neural network as an input to another in pytorch

I have a pretrained convolution neural network which produces and output of shape (X,164) where X is the number of test examples. So output layer has 164 nodes. I want to take this output and give this two another network which is simply a fully connected neural network whereby the first layer has 64 nodes and output layer has 1

Tag: conv-neural-network

Data type preference for training CNN?

Extracting Transfer learning output from CNN Keras

Problem with data cast on the GPU in PyTorch

RuntimeError: Given groups=1, weight of size [32, 16, 5, 5], expected input[16, 3, 448, 448] to have 16 channels, but got 3 channels instead

How to add a traditional classifier(SVM) to my CNN model

Giving output of one neural network as an input to another in pytorch

Traing a CNN using Prelu activation function

TensorFlow CNN Incompatible Shapes: 4D input shape

Pytorch: 1D target tensor expected, multi-target not supported

Why do sometimes CNN models predict just one class out of all others?