Aveen Dayal

Papers

Total Citations

132

H-Index

About

Dr. Aveen Dayal is a leading researcher at the intersection of computer vision, deep learning, and edge computing, with a primary focus on advancing human-computer interaction and assistive technologies. Her most impactful work centers on robust hand gesture and sign language recognition, uniquely leveraging thermal imaging to overcome the limitations of traditional RGB-based systems, such as poor lighting and privacy concerns. Dr. Dayal’s pioneering contributions include the development of a deep learning-based system for sign language digits recognition from thermal images, which has garnered 70 citations, and a robust deep CNN framework for general hand gesture recognition using thermal data, cited 62 times. These innovations are critical for applications ranging from medical assistive technologies and human-robot interaction to crisis management and contactless communication. By integrating these models with edge computing systems, she has enabled real-time, low-latency processing, making her work highly practical for deployment in resource-constrained environments. Her research not only pushes the boundaries of non-invasive sensing but also directly enhances accessibility and safety in critical fields, establishing her as a key figure in the evolution of intelligent, privacy-preserving interfaces.