M M Nabi

Papers

1

Total Citations

13

H-Index

1

About

Dr. M M Nabi is a rising researcher in computational ecology and marine biology, with a primary focus on developing machine learning solutions for aquatic species monitoring. Their most cited work, "Semi-supervised learning for fish species recognition" (2023, 13 citations), addresses a critical challenge in fishery industries: accurate and robust species classification and detection. By leveraging semi-supervised learning techniques, Dr. Nabi enables effective fish species recognition even with limited labeled data, significantly improving the monitoring of fish activities and distribution patterns. This work is particularly vital for identifying endangered species and supporting conservation efforts. Their contributions bridge the gap between advanced artificial intelligence and practical ecological applications, offering scalable tools for automated underwater surveillance. Dr. Nabi’s research holds promise for transforming how fisheries manage resources, enhance sustainability, and protect biodiversity. With a growing citation record and a focus on real-world impact, they are establishing themselves as an innovative voice at the intersection of computer vision and marine science, poised to influence both academic research and industry practices in aquatic ecosystem management.

Research Focus

Key Achievements

1
H-Index
1
Papers
13
Total Citations
13
Avg Citations/Paper
🏆 Most Cited Paper
Semi-supervised learning for fish species recognition
13 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 8

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago