Tanuja Jha

Papers

Total Citations

H-Index

About

Tanuja Jha is a researcher in Human-Computer Interaction (HCI) and computer vision, with a focus on developing intuitive, vision-based systems for robotic control. Her most-cited work, "Real Time Hand Gesture Recognition for Robotic Control" (2018), introduces a gesture recognition approach that enables natural, contact-free interaction between humans and machines. By leveraging computer vision techniques, Jha's research addresses key challenges in automating machine vision applications, offering a more accessible and efficient communication channel for users. Though early in her career, with this paper garnering 3 citations, her work contributes to the growing field of gesture-based HCI, which has implications for assistive technologies, industrial automation, and smart environments. Jha's research underscores the potential of vision-based interfaces to replace traditional input methods, making technology more seamless and inclusive. Her contributions are particularly relevant for students and researchers exploring the intersection of machine learning, real-time processing, and human-robot interaction.