Mohammad Shorif Uddin
Papers
7
Total Citations
94
H-Index
5
About
Mohammad Shorif Uddin is a pioneering researcher at the intersection of computer vision, artificial intelligence, and smart agriculture. His work focuses on developing automated systems for agricultural quality assessment, particularly using machine learning to classify fruit maturity and detect defects. Uddin’s major contributions include creating comprehensive, real-world image datasets for dragon fruit and tomatoes—enabling more accurate AI models for agricultural grading. His 2023 dragon fruit dataset paper has already garnered 34 citations, while his tomato dataset work has earned 10 citations, reflecting the growing demand for practical AI solutions in food production. Beyond agriculture, Uddin has explored the role of AI in public health, contributing to frameworks for combating the COVID-19 pandemic. He has also authored influential surveys on robots and drones in agriculture, as well as harvesting robots, helping to shape the field of precision agriculture. Through his curated datasets and applied research, Uddin is bridging the gap between computer vision and real-world farming challenges, making him a key figure in the movement toward smarter, data-driven agriculture.
Research Focus
Key Achievements
Top Papers
- 1
- 2Proceedings of International Joint Conference on Computational Intelligence24 citations · 2019
- 3Robots and Drones in Agriculture—A Survey16 citations · 2021
- 4
- 5Harvesting Robots for Smart Agriculture5 citations · 2022
- 6
- 7