eLife

New idtracker.ai rethinks multi-animal tracking as a representation learning problem to increase accuracy and reduce tracking time

Identification of each animal in a collective becomes possible even when individuals are never all visible simultaneously, enabling faster and more accurate analysis of collective behavior.

The Deepfake Nudes Crisis in Schools Is Much Worse Than You Thought

An analysis by WIRED and Indicator found nearly 90 schools and 600 students around the world impacted by AI-generated ...

Law enforcement is trying to combat abusive AI. Experts say easier said than done

An Ohio man was convicted of cybercrimes involving obscene AI-generated images of women and children. But experts warn of the ...
PNAS

DeepDegradome: A structure-aware deep learning framework for PROTAC and ligand generation against protein targets

Targeted protein degradation, particularly using PROTACs, offers a promising strategy to treat diseases. However, designing effective PROTACs remains challenging due to limitations in current ...
IEEE

Nested Stacking TSK Fuzzy Classifier by Additive-Rule-Decomposition & Anti-Noisy-Labeling Based Learning on Large-Scale Noisy Labeling Data

Abstract: This study explores how to develop a novel deep stacking Takagi–Sugeno–Kang (TSK) fuzzy classifier to efficiently realize interpretable classification for large-scale multi-class complex ...
IEEE

LapGraph-CutFS: A Deep Learning-Based Framework for Multi-Class Classification of Maize Leaf Pests, Diseases, and Healthy States

Abstract: Monitoring crop health is a critical component of sustainable agriculture, enabling the early detection and effective management of pests and diseases. We propose LapGraph-CutFS, a ...