Rajveer Shastri

Papers

Total Citations

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About

Rajveer Shastri is a researcher specializing in computer vision and embedded systems, with a focus on underwater image processing and autonomous robotics. His most impactful work, the "CNN based color balancing and denoising technique for underwater images" (CNN-CBDT, 2023), addresses the critical challenges of color distortion and blurring caused by light scattering in aquatic environments. This paper has garnered 20 citations, highlighting its significance in improving underwater image analysis for applications like marine exploration and environmental monitoring. Shastri’s earlier work on a "Line Follower with Obstacle Information System Using ZigBee" (2018, 7 citations) demonstrates his versatility in robotics, where he developed a Firebird V robot that follows a white line on a black surface, detects obstacles, and wirelessly transmits alerts to a PC via ZigBee. This project showcases his ability to integrate sensing, control, and communication technologies. Together, his contributions reflect a commitment to solving real-world problems through innovative deep learning and hardware-software integration, making him a notable figure in both underwater imaging and autonomous systems research.