Mandar Datar
Papers
1
Total Citations
3
H-Index
1
About
Mandar Datar is a researcher specializing in computer vision and high-performance computing, with a particular focus on real-time stereo vision systems. His most cited work, "Accelerated Stereo Vision Using Nvidia Jetson and Intel AVX" (2021), demonstrates a novel approach to optimizing stereo depth estimation by leveraging both embedded GPU platforms (Nvidia Jetson) and CPU vectorization (Intel AVX). This contribution addresses the critical challenge of achieving real-time performance in resource-constrained environments, making stereo vision more practical for applications in robotics, autonomous navigation, and augmented reality. While his citation count is still growing, Datar’s work highlights a pragmatic, hardware-aware methodology that bridges the gap between algorithmic efficiency and deployment feasibility. His research is particularly valuable for students and engineers seeking to understand how to accelerate computer vision pipelines without sacrificing accuracy. As the demand for edge-computing solutions in AI continues to rise, Datar’s contributions offer a foundational reference for optimizing stereo vision on heterogeneous architectures.
Research Focus
Key Achievements
Top Papers
- 1Accelerated Stereo Vision Using Nvidia Jetson and Intel AVX3 citations · 2021