Abhishek Sethi

Papers

Total Citations

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About

Abhishek Sethi is a researcher in human-computer interaction and assistive technology, with a primary focus on gesture-based communication systems. His most cited work, "Ensembled Neural Network for Static Hand Gesture Recognition" (2021, 4 citations), addresses a critical gap in sign language interpretation by developing a robust machine learning framework that combines multiple neural network architectures. This research extends beyond traditional speech-impaired communication to applications in automated vehicle control, intelligent assistant systems, and human-robot interaction. Sethi's contribution lies in demonstrating how ensemble learning can improve the accuracy and reliability of static gesture recognition, making real-world deployment more feasible. His work bridges the gap between computer vision and accessibility, showing how deep learning can create more intuitive interfaces for diverse users. By focusing on practical, cross-domain applications, Sethi positions himself at the intersection of inclusive design and artificial intelligence, where his findings have implications for both assistive technology and mainstream human-machine interaction systems.