A. F. M. Shahab Uddin

Papers

1

Total Citations

32

H-Index

1

About

Dr. A. F. M. Shahab Uddin is a leading researcher at the intersection of artificial intelligence and sustainable agriculture, with a primary focus on precision crop management and deep learning applications. His most impactful work addresses a critical global challenge: ensuring food security through early and accurate detection of crop diseases. In his highly cited 2023 study, "Enhancing Rice Crop Management: Disease Classification Using Convolutional Neural Networks and Mobile Application Integration," Dr. Uddin pioneered a novel approach that overcomes the limitations of traditional RGB-based image processing. By integrating a custom CNN architecture with a user-friendly mobile application, his system enables farmers to diagnose rice diseases in real-time with significantly improved reliability. This work, which has already garnered 32 citations, demonstrates his commitment to translating complex computational models into accessible, on-the-ground tools. Dr. Uddin’s contributions are particularly notable for bridging the gap between advanced machine learning and practical agricultural needs, offering a scalable solution to mitigate yield losses. His research continues to shape the future of smart farming, empowering stakeholders with data-driven insights to enhance productivity and global food security.

Research Focus

Key Achievements

1
H-Index
1
Papers
32
Total Citations
32
Avg Citations/Paper
🏆 Most Cited Paper
Enhancing Rice Crop Management: Disease Classification Using Convolutional Neural Networks and Mobile Application Integration
32 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 6

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago