Learn With Jay on MSNOpinion

Momentum optimizer explained for faster deep learning training

In this video, we will understand in detail what is Momentum Optimizer in Deep Learning. Momentum Optimizer in Deep Learning ...
Learn With Jay on MSNOpinion

Deep learning regularization: Prevent overfitting effectively explained

Regularization in Deep Learning is very important to overcome overfitting. When your training accuracy is very high, but test ...
eLife

Separating selection from mutation in antibody language models

This important study introduces a new biology-informed strategy for deep learning models aiming to predict mutational effects in antibody sequences. It provides solid evidence that separating ...
Open Heart

Development and validation of a deep learning model for severe mitral stenosis detection from chest X-rays

Background Although chest X-rays (CXRs) are widely used, diagnosing mitral stenosis (MS) based solely on CXR findings remains ...
Semiconductor Engineering

DL Atomistic Semi-Empirical Pseudopotential Model For Nanomaterials (UC Berkeley, LBNL et al.)

A new technical paper titled “Deep-learning atomistic semi-empirical pseudopotential model for nanomaterials” was published ...
EurekAlert!

From time series to a single snapshot: A smarter way to track wheat growth in real time

A research team has introduced a lightweight artificial intelligence method that accurately identifies wheat growth stages ...
Frontiers

Advances in Deep Learning–Based Intelligent Sensing for Non-Destructive Monitoring of Crop Nutrition and Quality

Crop nutrition and quality formation are complex processes influenced by genotype, environment, and management practices.

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 ...
Security Boulevard

NDSS 2025 – DLBox: New Model Training Framework For Protecting Training Data

Jaewon Hur (Seoul National University), Juheon Yi (Nokia Bell Labs, Cambridge, UK), Cheolwoo Myung (Seoul National University), Sangyun Kim (Seoul National University), Youngki Lee (Seoul National ...
News-Medical.Net on MSN

Automated system improves deep learning accuracy in chest radiography analysis

Researchers at Osaka Metropolitan University have discovered a practical way to detect and fix common labeling errors in ...

Automatic label checking: The missing step in making medical AI reliable

Researchers at Osaka Metropolitan University have discovered a practical way to detect and fix common labeling errors in ...