Tag: channel attention

Researchers developed a computer vision and pose estimation framework combining YOLOv8s localization and 17-keypoint skeleton tracking to jointly predict jianzi ...

An integrated artificial intelligence framework combining generative oversampling, multi-scale attention, and dynamic focal loss achieved 95.88 percent classification accuracy on ...

A dual-channel AI framework that fuses raw byte textures with statistical flow features achieved 98.74 percent accuracy on real urban ...

A new MLP-based segmentation method combining mixer layers with channel attention achieved a Dice coefficient of 81.45 percent on the ...

A deployment-efficient CNN-LSTM framework with channel attention detects encrypted, imbalanced, and heterogeneous malicious traffic in real time on CPU-only hardware, ...

Researchers have built a lightweight AI system that detects epileptic seizures in EEG recordings from patients it has never seen, ...

A new lightweight deep learning framework called LCASP-MMANet achieves state-of-the-art sign language recognition accuracy while remaining efficient enough for real-world, ...

A new multi-scale deep learning framework called Rain-PostEFNet substantially improves numerical weather prediction rainfall forecasts, with the largest gains in ...

Researchers at Harbin Institute of Technology have shown that sensors inside ordinary buildings, combined with building-specific hybrid deep learning models, ...

Researchers at IIITDM Kancheepuram have developed DECA-YOLO, a lightweight dual-pooling channel attention enhancement to YOLOv7 that improves real-time pedestrian detection ...