Benchmark of 1.4 million checked protein structures could sharpen AI predictions

University of Missouri researchers have released the world's largest collection of protein models with quality assessment—a groundbreaking new resource that could accelerate drug development for ...
TMCnet

Data Normalization vs. Standardization: What's the Difference and When to Use Each

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and data preprocessing. If you''ve ever built a predictive model, worked on a ...
Hosted on MSN

Local Response Normalization (LRN) in Deep Learning Explained

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 ...
www.cs.utexas.edu

Hyperspherical Normalization for Scalable Deep Reinforcement Learning

@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 ...
Scientific Research Publishing

Luo, H., Jiang, W., Gu, Y., Liu, F., Liao, X., Lai, S., et al. (2020) A Strong Baseline and Batch Normalization Neck for Deep Person Re-Identification. IEEE Transactions on ...

ABSTRACT: With the advancement of technology and the growth of human demand, pedestrian re-identification is a key technology of intelligent systems and plays an important role in daily life.
IEEE

Pseudoinverse Learning Algorithm As a Unified Framework For Normalization In Deep Learning

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 ...
Frontiers

A lightweight multi-deep learning framework for accurate diabetic retinopathy detection and multi-level severity identification

Accurate and timely detection of diabetic retinopathy (DR) is crucial for managing its progression and improving patient outcomes. However, developing algorithms to analyze complex fundus images ...
marktechpost

Dynamic Tanh DyT: A Simplified Alternative to Normalization in Transformers

Normalization layers have become fundamental components of modern neural networks, significantly improving optimization by stabilizing gradient flow, reducing sensitivity to weight initialization, and ...