Category "neural-network"

Deep neural network gives a constant value as output

I have implemented a neural network from scratch. I have taken random values as both input and output. When I use a single layer( with sigmoid activation) the n

Faster RCNN - Number of epochs impact inference time

I have trained two Faster RCNN models with the exact same parameters with the exception of: Model 1: 150 epochs Model 2: 5 epochs Once the models have been trai

Bayesian Optimization for hyperparameter tuning

I have a problem with this code. I need to optimize dropout rate and learning rate. My code is reported below but the optimizer = BayesianOptimization() doesn't

CUDA cuDNN: cudnnGetConvolutionForwardWorkspaceSize fails with bad parameter

I am currently trying to implement a very basic 2D convolution using CUDA cuDNN between an "image" of size 3x3 and a kernel of size 2x2, resulting in a 2x2 outp

Group of structured binding errors, pertains to neural networking

so i downloaded a library that hasnt been in use in years, for Neural Evolutionary Augmenting Topologies. Basically, a neural network that evolves. It came with

How do you implement SVoice?

I'm trying to use Facebook's SVoice to split out different speakers in my audio file using python. I found a library that implemented it here: https://github.co

Loss function for changing a classification network to a regression one

I am trying to change a neural network that classifies pointclouds into 40 different classes, to a regression networks that predicts a specific property of them

Feature importance in neural networks with multiple differently shaped inputs in pytorch and captum (classification)

I have developed a model with three inputs types. Image, categorical data and numerical data. For Image data I've used ResNet50 for the other two I develop my o

Neural network: same prediction for different inputs

I am getting the same prediction for different inputs. I am trying to use a regressional neural network. I want to predict values instead of class using neural

Pytorch transfer learning accuracy and lossess not improving. Resnet 50 and Cifar-10

I have been trying everything to fix this issue however my results are still the same, my validation accuracy, train_loss, val_loss are not improving. I have no

"Module not Found Error : No module named albumentations"

I'm writing a code with albumentations function and it will give me this error ModuleNotFoundError: No module named 'albumentations' I also installed this pack

Training loss much lower than test loss even though it's using the same data

I'm using the same data for training and testing (which isn't best practice), and in theory the loss should be exactly the same. However, when training, my loss

Loss function in Faster-RCNN

I read many articles online today about fast R-CNN and faster R-CNN. From which i understand, in faster-RCNN, we train a RPN network to choose "the best region

Importing Adam and ImageDataGenerator on google colab failed

I'm implementing a UNet neural network but I'm having some issues while importing libraries. I found a solution for a couple of them, but I still have a problem

Dividing a large file into smaller ones for training

I have a very large file and I want to divide it into smaller ones for training. I've read about pickle files, so I split the large file into training-validatio

Loop over hidden layer's nodes and create model based on MLP

I want to build an MLP classifier on iris dataset. Actually, I want to build a function that runs the model with N hidden units in the hidden layer and a loop t

how to score part of the neural network once and the rest multiple times caching the intermediate layer?

I train a model A and try to use the output of the intermediate layer with the name="layer_x" as an additional input for model B. model A is using input1, and m

Training of Siamese Network with Contrastive Loss Misses Parameter Updates

I try to implement a rather simple siamese network and a contrastive loss function. I use a pre-trained VGG16 as a backbone model and strip away the last ReLU a

Define flatten layer in neural network using pytorch

I'm trying to define a flatten layer before initiating fully connected layer. As my input is a tensor with shape (512, 2, 2), so I want to flatten this tensor b

Trouble extracting numbers from helib::Ctxt ciphertext

I'd like to access directly to the numbers composing the ciphertext Ctxt from HElib, but reading the documentation I don't seem to find anything that can help m

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