IEEE

SmartLeafNet: An Automated Deep Learning based Efficient Plant Disease Detection using RNN-GRU Model

Abstract: Plant leaf disease has consequences for health and productivity maintenance, hence making early interventions on them possible, and preventing loss caused by disease. They minimize the usage ...
Science Daily

NASA’s Perseverance rover completes the first AI-planned drive on Mars

NASA’s Perseverance rover has just made history by driving across Mars using routes planned by artificial intelligence instead of human operators. A vision-capable AI analyzed the same images and ...
News-Medical.Net

Integrated Monte Carlo and deep learning improve radiotherapy QA

Led by Professor Fu Jin, the study addresses a critical challenge in radiation therapy: balancing the computational speed and ...
Morning Overview on MSN

Google DeepMind AI lights up the dark genome and flags risky DNA tweaks

Google DeepMind’s latest artificial intelligence model is turning the most mysterious stretches of human DNA into readable text, and in the process, it is flagging which tiny edits could tip a cell ...

Deep-learning algorithms enhance mutation detection in cancer and RNA sequencing

Researchers from the Faculty of Engineering at The University of Hong Kong (HKU) have developed two innovative deep-learning ...
IEEE

PF-DTN: Predictive routing for intelligent delay tolerant networks using RNN-LSTM deep learning with monte carlo dropout uncertainty estimation and hybrid deterministic ...

Abstract: Delay tolerant networks (DTN/s) represent an evolution of traditional ad hoc networks, specifically designed for extreme environments characterized by intermittent connectivity, ...
EurekAlert!

AI-based system for real-time detection of whip sounds in horse racing

Regulations limit both the intensity and frequency of whip use during horse racing. Nevertheless, compliance is currently verified manually after each race. Researchers at University of Tsukuba have ...
Business Insider

Minkang Zhang Improves Medical Image Recognition Through RNN Optimization and Deep Learning Integration

A deep learning framework enhances medical image recognition by optimizing RNN architectures with LSTM, GRU, multimodal fusion, and CNN integration. It improves dynamic lesion detection, temporal ...
digitalmarketreports

Minkang Zhang Improves Medical Image Recognition Through RNN Optimization and Deep Learning Integration

The exponential increase in medical imaging data has intensified the need for accurate and efficient diagnostic analysis. Conventional methods often fail to process large volumes of dynamic images ...
Frontiers

Review of deep learning models with Spiking Neural Networks for modeling and analysis of multimodal neuroimaging data

Medical imaging has become an essential tool for identifying and treating neurological conditions. Traditional deep learning (DL) models have made tremendous advances in neuroimaging analysis; however ...
GitHub

Deep Asymmetric Recurrent Networks in JAX.

darnax is a research library for building and experimenting with asymmetric recurrent neural networks and their learning dynamics. Inspired by recent work on local plasticity and representational ...