Md Modasshir

Papers

Total Citations

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About

Md Modasshir is a researcher at the forefront of applying artificial intelligence to marine science, with a primary focus on underwater computer vision and autonomous systems. His work centers on developing deep learning and semi-supervised learning methods to address the critical challenge of coral reef monitoring—a task complicated by the difficulty of obtaining expert annotations for rare or ambiguous coral species. His most-cited paper, "Enhancing Coral Reef Monitoring Utilizing a Deep Semi-Supervised Learning Approach" (2020, 28 citations), introduces a novel framework that reduces reliance on labeled data, enabling more robust detection in data-scarce environments. Complementing this, his 2018 study "Coral Identification and Counting with an Autonomous Underwater Vehicle" (27 citations) pioneers the integration of deep neural networks with low-cost AUVs for automated population surveys, directly aiding environmental assessment. Additionally, his comparative analysis "Deep Neural Networks: A Comparison on Different Computing Platforms" (2018, 25 citations) provides foundational insights into deploying DNNs efficiently across hardware, supporting real-time underwater applications. With over 80 combined citations, Modasshir’s contributions are instrumental in bridging AI and marine biology, offering scalable tools for coral conservation and autonomous underwater exploration.