Jeshwanth Reddy Depa
Papers
1
Total Citations
3
H-Index
1
About
Jeshwanth Reddy Depa is a researcher at the forefront of computer vision and human-computer interaction, with a focused expertise in deep learning applications for assistive technology. His most cited work, "Vision-based Hand Gesture Recognition for Indian Sign Language Using Convolution Neural Network" (2023), has garnered 3 citations and represents a significant contribution to bridging communication gaps for the hearing-impaired community. Depa’s research centers on developing robust, real-time gesture recognition systems using convolutional neural networks (CNNs), addressing the unique challenges of Indian Sign Language (ISL) which has distinct grammatical and spatial features. By leveraging vision-based approaches over sensor-dependent methods, his work enhances accessibility and scalability, making assistive technology more practical for widespread use. Published in the peer-reviewed International Journal of Computer Science Engineering and Its Research Trends (IJCERT), this study demonstrates Depa’s commitment to creating socially impactful AI solutions. His contributions not only advance the field of computer vision but also underscore the potential of deep learning in inclusive technology design, offering a foundation for future research in sign language recognition and human-robot interaction.
Research Focus
Key Achievements
Top Papers
- 1