Tag: real-time detection

A new integrated framework combining quantum-inspired optimization and deep learning achieves high accuracy in detecting diverse cyberattacks across major cloud ...

An improved YOLOv8-based detector reaches 79.8% mAP50 on a synthetic forest wildfire benchmark with 2.52 million parameters while running at ...

A systematic review of 44 YOLO-based railway track defect detection studies finds that none demonstrates fully operational deployment, with all ...

A new AI framework combining attention-enhanced YOLOv8 and Bald Eagle Optimization achieved 98.94% accuracy in detecting transmission and distribution faults ...

PVFire-YOLO, a real-time detection framework with attention-enhanced multiscale fusion, reaches 87.4% mean average precision on a new photovoltaic fire dataset ...

University of Maryland researchers used EEG to identify statistically significant brain wave changes linked to cybersickness from the vergence-accommodation conflict ...

A new adaptive Kalman filtering method frames sleep spindle detection as state-space inference, producing interpretable, low-latency sigma-event catalogues from full-night ...

Researchers at Fujian Agriculture and Forestry University have developed GDE-YOLO, a lightweight deep learning model that detects tea leaf diseases ...

A lightweight hybrid framework combining randomized convolutional feature extraction with extreme learning machines classifies vehicles in fog, rain, and drone ...