Harshadkumar B. Prajapati

Papers

Total Citations

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About

Harshadkumar B. Prajapati is a computer vision researcher whose work focuses on the intersection of deep learning and human-machine interaction. His primary research areas include facial expression recognition (FER) and scene classification, where he leverages convolutional neural networks (CNNs) to solve complex visual understanding problems. His most influential work, a 2019 survey on face expression recognition using CNNs, has garnered 54 citations, establishing him as a key voice in this rapidly evolving field. In this survey, he systematically analyzed the challenges of accurate FER—critical for applications in robotics, education, artificial intelligence, and security—and categorized the major approaches used to address them. Building on this foundation, Prajapati proposed a concise CNN architecture in 2021 that demonstrates efficient and effective FER performance, contributing to the advancement of human-machine interaction systems. His 2020 survey on scene classification techniques further showcases his breadth, exploring how scene understanding can power surveillance, autonomous driving, and robotics. Through his surveys and novel architectures, Prajapati has provided both foundational knowledge and practical solutions for researchers and engineers working to make machines more perceptive of human expressions and environments.