Tag: computer vision

A newly published study describes a unified YOLOv11–EfficientViT neural network that jointly detects traffic lights and signs and recognizes traffic ...

An enhanced RT-DETR-ResNet18 framework raises detection accuracy for camouflaged soybean pests, reaching 77.4% mAP@0.5 across 12 pest categories.

A dual-path attention fusion network combining Swin Transformer and frozen DINOv2 features reached 99.24% accuracy on a leakage-screened hold-out test ...

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

Researchers developed a lightweight SAR building segmentation framework that achieves high accuracy while maintaining computational efficiency for urban mapping.

A new ensemble deep learning framework called EnPreNiNet, paired with a night image enhancement technique, achieved a reported mean Average ...

A lightweight hybrid transformer model combining wavelet transforms with MobileViT achieved over 99% accuracy in classifying plant diseases across four ...

A genetically optimized U-Net framework segments athletes' bodies in video with high accuracy and flags visually abnormal knee, ankle, and ...

A new study shows that a frozen CLIP vision-language model with lightweight adapters can improve human activity recognition in low-light ...

A systematic review of 59 studies finds deep learning dominates fungal leaf disease detection while bacterial diagnosis, generative AI and ...