S Srikanth

Papers

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About

S. Srikanth is a researcher advancing the field of computer vision, with a primary focus on depth and dimension estimation—a critical capability for applications in robotics, autonomous navigation, and the construction industry. Their most-cited work, "Depth and Dimension Estimation Using Computer Vision" (2025), tackles the fundamental challenge of enabling machines to perceive three-dimensional space from two-dimensional images. Srikanth addresses persistent obstacles in monocular depth estimation, including scale ambiguity and data scarcity, proposing innovative methods to improve measurement accuracy without relying on expensive multi-camera setups. With 9 citations to this key paper, their contributions are gaining traction among peers seeking practical solutions for real-world spatial perception. By bridging the gap between algorithmic theory and industrial application, Srikanth’s research lays essential groundwork for safer autonomous vehicles and more precise robotic manipulation. Their work stands as a valuable resource for students and engineers aiming to understand how machines can interpret depth from limited visual data, marking Srikanth as a promising voice in the ongoing evolution of intelligent vision systems.