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.
EurekAlert!

Lightweight framework boosts cross-domain microseismic signal classification for underground engineering

Struggling with microseismic signal classification in deep underground engineering? Researchers from Sichuan University ...
AZoRobotics

Detecting IoT Malware in EV Chargers with Deep Learning

A new study presents a deep learning approach for IoT malware detection in EV charging stations, addressing key limitations ...
IEEE

Spectral Selection Convolution and Overlapped-Centering Mamba Network for Hyperspectral Image Classification

Abstract: Hyperspectral image (HSI) classification is a critical task in remote sensing. Recently, deep learning (DL) methods, particularly state space models (SSMs) like Mamba, have garnered ...
The Lancet

Deep learning on histopathological images to predict breast cancer recurrence risk and chemotherapy benefit: a multicentre, model development and validation study

aTaub Faculty of Computer Science, Technion-Israel Institute of Technology, Haifa, Israel bFaculty of Electrical and Computer Engineering, Technion-Israel Institute of Technology, Haifa, Israel ...
IEEE

QueenNet: Quantum-Enhanced Neural Network for Hyperspectral Image Classification

Abstract: Hyperspectral image (HSI) classification is a critical task in the field of remote sensing. Existing deep learning models have made significant progress in HSI classification, but often ...
Frontiers

Editorial: Application of deep learning in biomedical image processing

In the era of data-driven medicine, biomedical imaging has evolved from a purely diagnostic tool to a cornerstone of precision healthcare. The confluence of deep learning (DL) and biomedical image ...