Jose Sousa

Papers

Total Citations

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About

Jose Sousa is a researcher at the forefront of integrating computer vision, deep learning, and bio-inspired robotics. His work centers on developing intelligent systems that bridge the gap between human gesture and machine control, with a particular focus on robotic manipulation. In his most cited work (5 citations), Sousa introduced a novel three-stage computer vision system that combines feature matching, edge detection, and deep learning to enable precise hand gesture classification for robotic arm control. This framework demonstrates a practical pathway for intuitive human-robot interaction. Expanding on this, his second highly cited paper (4 citations) explores the use of fractional calculus for gesture segmentation in bio-inspired robotic models, achieving improved recognition rates for complex, segmented movements. By applying advanced mathematical techniques to gesture recognition, Sousa contributes to more fluid and natural control of biomimetic robots. His research holds significant promise for applications in assistive robotics, industrial automation, and human-robot collaboration, establishing him as a rising voice in the fields of pattern recognition and intelligent control systems.