After verifying the redundancy characteristics of the final activation function, linear layer, and the number of channels by eigen-values analysis of latent features and experiments, we propose a ...

There are 50000 training images and 10000 test images in this dataset. For more information on the CIFAR10 dataset and its preprocessing for a convolutional neural network, please read my article ‘ ...

Convolutional Neural Network(CNN) is a neural network architecture in Deep Learning, used to recognize the pattern from structured arrays. However, over many years, CNN architectures have evolved.

Exploiting invariances in data is crucial for neural networks to learn efficient representations and to make accurate predictions. Translation invariance is a key symmetry in image processing and lies ...

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI.