Mayoori K Bhat

Papers

Total Citations

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About

Mayoori K Bhat is a researcher in computer vision and deep learning, with a primary focus on human action recognition. Her most-cited work, "Human Action Recognition using Deep Learning Technique" (2023), introduces a novel approach that combines Mediapipe for decoding human posture and movement with Long Short-Term Memory (LSTM) networks for temporal sequence learning. This method addresses the challenging task of identifying human activities from video data, offering an efficient and accurate solution for real-world applications such as surveillance, human-computer interaction, and assistive technologies. With 2 citations, this paper represents a foundational contribution to the field, showcasing her ability to integrate lightweight pose estimation with robust deep learning architectures. Bhat’s work stands out for its practical emphasis on leveraging Mediapipe’s real-time capabilities, making action recognition more accessible and computationally efficient. Her research bridges the gap between theoretical advances in deep learning and applied computer vision, providing a scalable framework for activity analysis. As an emerging scholar, Bhat’s contributions hold promise for advancing intelligent systems that interpret human behavior, with potential impact across robotics, healthcare, and smart environments.