Bridging communication gaps between hearing and hearing-impaired individuals is an important challenge in assistive ...

Understand Local Response Normalization (LRN) in deep learning: what it is, why it was introduced, and how it works in convolutional neural networks. This tutorial explains the intuition, mathematical ...

@InProceedings{pstone_simba, author = {Hojoon Lee and Youngdo Lee and Takuma Seno and Donghu Kim and Peter Stone and Jaegul Choo}, title = {Hyperspherical Normalization for Scalable Deep Reinforcement ...

Russia expects sanctions relief as President Trump directs officials to identify restrictions that could be lifted—a startling but not surprising policy shift that comes shortly after the White House ...

Batch Normalization (BN) is a widely used technique that helps to accelerate the training of deep neural networks and improve model performance. By normalizing the inputs to each layer so that they ...

ABSTRACT: Pneumonia remains a significant cause of morbidity and mortality worldwide, particularly in vulnerable populations such as children and the elderly. Early detection through chest X-ray ...

Abstract: In recent years, several normalization methods have been proposed in order to train neural networks, including batch normalization, layer normalization, weight normalization, and group ...

Abstract: Social media platforms, such as Twitter, produce significant quantities of textual data, providing important opportunities for the analysis of emotions. The identification of emotions within ...