A new spike-based image model enables accurate hand gesture recognition by capturing dynamic motion patterns using neural-inspired data processing.

A research paper by scientists at Shanghai Jiao Tong University presented a novel channel-wise cumulative spike train image-driven model (cwCST-CNN) for hand gesture recognition.

Scientists introduce a method using programmable metasurfaces to achieve highly accurate, wireless hand gesture recognition, overcoming challenges in existing technologies.

Scientists have developed an Artificial Intelligence (AI) system that recognises hand gestures by combining skin-like electronics with computer vision.

Scientists from Nanyang Technological University, Singapore (NTU Singapore) have developed an Artificial Intelligence (AI) system that recognises hand gestures by combining skin-like electronics with ...

Gesture recognition by BeEmotion, an innovator at the intersection of AI and human behavior that provides cutting-edge solutions to enhance interaction, prevent accidents, and bring enjoyment to ...