Papers
1
Total Citations
8
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1
About
Dr. Rajesh Ingle is a leading researcher in artificial intelligence and human motion analysis, with a particular focus on integrating temporal and spatial deep learning models. His most-cited work, "Fusion of Temporal Transformer and Spatial Graph Convolutional Network for 3-D Skeleton-Parts-Based Human Motion Prediction" (2024), addresses a critical challenge in intelligent surveillance and human–robot interaction: accurately predicting full-body human motion by capturing complex joint interactions and diverse movement patterns. This paper, garnering 8 citations in its first year, exemplifies his innovative approach to fusing transformer architectures with graph convolutional networks, significantly advancing the state of the art in 3-D skeleton-based prediction. Dr. Ingle’s contributions are pivotal for developing more responsive and intuitive autonomous systems. His work continues to shape the future of human-centered AI, making him a key figure for students and researchers exploring the intersection of computer vision, robotics, and spatiotemporal modeling.
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