Aadarsh Sampath
Papers
1
Total Citations
5
H-Index
1
About
Aadarsh Sampath is a researcher whose work lies at the intersection of computer vision and machine learning, with a particular focus on object recognition in real-world environments. His most cited study, "A Study of Household Object Recognition Using SIFT-Based Bag-of-Words Dictionary and SVMs" (2015), demonstrates a practical approach to enabling machines to identify everyday items by combining Scale-Invariant Feature Transform (SIFT) with a bag-of-words model and support vector machines. This work, which has garnered 5 citations, addresses a key challenge in robotics and smart home applications—how to make object recognition robust and efficient in cluttered, dynamic household settings. By leveraging classical computer vision techniques, Sampath’s research contributes to foundational methods that balance accuracy with computational feasibility. His findings are particularly relevant for students and researchers exploring low-cost, scalable solutions for autonomous systems. While his citation count reflects a focused, early-career impact, the practical nature of his work underscores its potential for integration into assistive technologies and domestic robotics, offering a stepping stone for further innovation in scene understanding and human-robot interaction.
Research Focus
Key Achievements
Top Papers
- 1