Satish Chand
Papers
4
Total Citations
59
H-Index
2
About
Satish Chand is a researcher whose work bridges the critical fields of computer vision, agricultural technology, and robotics. His primary contributions lie in advancing text detection and extraction from natural scene images—a foundational task for applications like autonomous navigation and automatic number plate recognition. His 2018 paper on a "text awareness score" for detection and localization has garnered 39 citations, establishing a key methodology in the field. More recently, Chand has applied deep learning to precision agriculture, developing a weed classification system for corn that integrates an improved attention mechanism with Explainable AI (XAI) techniques, a 2024 work already cited 17 times. This focus on transparency in AI models is particularly notable for real-world deployment. Demonstrating a practical engineering bent, Chand is also involved in creating indigenously developed robotic devices for inspecting critical power plant components, addressing the growing energy demand. His research trajectory—from foundational image analysis to applied, explainable AI and tangible robotic solutions—showcases a commitment to solving complex, real-world problems with measurable impact.
Research Focus
Key Achievements
Top Papers
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- 3Text Region Extraction From Scene Images Using AGF and MSER2 citations · 2020
- 4