A zero-shot learning framework for maize cob phenotyping

A new study presents a zero-shot learning (ZSL) framework for maize cob phenotyping, enabling the extraction of geometric ...

Inference is splitting in two — Nvidia’s $20B Groq bet explains its next act

Nvidia’s $20 billion strategic licensing deal with Groq represents one of the first clear moves in a four-front fight over ...
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 ...
IEEE

BNResNet: Batch Normalization-Inspired Deep Bottleneck Residual Architecture for Aerial Scene Recognition in Low-Contrast Remote Sensing Images

Abstract: Remote sensing (RS) images are evolving daily for their applications in surveillance, planned urbanization, law enforcement, climate change detection, agriculture, and monitoring ...
Game Rant

Dune Awakening Things You Should Always Carry in the Deep Desert

Lucas is a writer and narrative designer from Argentina with over 15 years of experience writing for games and news. He keeps a watchful eye at the gaming world and loves to write about the hottest ...
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

Protein structure prediction via deep learning: an in-depth review

The application of deep learning algorithms in protein structure prediction has greatly influenced drug discovery and development. Accurate protein structures are crucial for understanding biological ...
GitHub

Add batch&group&instance&layer normalization

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 ...