I have been working on Images for few months for my internship, and recently I have been wondering that is there a mathematical way of resizing the images. This
I'm trying to make a denoise autoencoder wherein the encoder part is vgg16 and decoder is opposite of vgg16(encoder) network. My dataset consists of 5K images i
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
I'm working on authorship detection from text task, I'm doing this by using a data frame consisting of symbol n-gram that I created using about 110k of 147 diff
Normally if I understood well PyTorch implementation of the Conv2D layer, the padding parameter will expand the shape of the convolved image with zeros to all f
I am trying to create a confusion matrix for my test set. My test set consists of 3585 images. Whenever I try to run the following code: x_test,y_test = next(it
I am trying to predict the of number peaks in time series data by using a CNN and keep on getting a data shape error. My data looks as follows: X = list of 520
My data contains 520 time series, each of length 2297: X_train = numpy.ndarray of shape (338, 2297, 1) X_val = numpy.ndarray of shape (85, 2297, 1) X_test = num
My model is already trained and is saved in model_trained.pkl file. And I'm trying to test the same using video captures. But getting error "FileNotFoundError:
I am working on a CNN architecture with an image RGB dataset that belongs to two categories, i.e., crops and another one is grass. However, I am concerned about
hello everyone i am trying to train a model using cnn and keras but the training don't finish and i got this warning and it stops training , i don't know why an
Suppose we have a matrix and we want to add a padding of 2 (we need to divide the padding on all side of the matrix ) in the case of padding=2 (add one at right
fellow coders. I am trying to figure out ways to add a confusion matrix to the output of my Mobilenet-based multiclass classifier. Being a biologist with limite
I came across this paper by some Facebook researchers where they found that using a softmax and CE loss function during training led to improved results over si
I have been working on a tensorflow model that predicts short term positive and negative trends in the stock market using momentum indicators. I have the model
I’m training a U-Net (model below) to predict 4 heatmaps (gaussian centered around a keypoint, one in each channel). Each channel is for some reason outpu
screenshot showing the model training stuck at epoch 1 without throwing error I am using google colab pro and here is my code snippet batch_size = 32 img_heigh
I want to use an image segmentation program which use CNN and fuse it with another lane detection network. Is it possible to train these two networks separately
I had around 360 images splitted %25 as validation data. I could train Deeplabv3 with those images without any issue. Later on I have added around 40 images wi
I am fairly new to coding and getting confused between average accuracy and overall accuracy. I have created a function to calculate accuracy, i then divide thi