Aisha Farooq

You are already at the latest version The given research paper is an end-to-end architecture of grayscale clothing image classification with a lightweight Convolutional Neural Network (CNN) with the Fashion-MNIST dataset. Its architecture consists of three convolutional layers with Batch normalization to stabilize training, Dropout to avoid overfitting, MaxPooling to reduce spatial, and data augmentation (random rotation, shifting, zooming, flipping) to increase the effective training set.