Mahamudul Hasan
Papers
2
Total Citations
29
H-Index
2
About
Mahamudul Hasan is a researcher at the forefront of applying artificial intelligence and robotics to critical challenges in food safety and agricultural automation. His work focuses on developing intelligent, real-time quality control systems that combine deep learning with robotic manipulation. Hasan’s major contributions include creating an XAI-enhanced deep learning framework for the real-time sorting of broiler chicken meat, using LIME to make the AI’s freshness detection decisions transparent and trustworthy. He has also pioneered a system for fish freshness detection and automatic removal of rotten fish, employing a Mask R-CNN method integrated with a robotic arm and fisheye analysis—a vital innovation for major fish-exporting nations like Bangladesh. His most cited papers, from 2024, have already garnered 16 and 13 citations respectively, demonstrating immediate impact. By automating these traditionally manual and error-prone inspection processes, Hasan is helping to reduce health hazards, ensure compliance with international standards, and enhance economic stability in the global food supply chain.
Research Focus
Key Achievements
Top Papers
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- 2