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 ...

Based on this observation, they proposed a new scaling method that uniformly scales all dimensions of depth, width and resolution of the network. They used the neural architecture search to design a ...

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.