Adane Nega Tarekegn

Norwegian University of Science and Technology

Papers

Total Citations

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About

Adane Nega Tarekegn is a researcher at the forefront of computer vision and deep learning, with a particular focus on underwater robotics and autonomous systems. His work centers on enhancing the perception capabilities of autonomous underwater vehicles (AUVs) through advanced image processing and object detection techniques. Tarekegn’s most impactful contribution, “Underwater Object Detection using Image Enhancement and Deep Learning Models” (2023, 14 citations), addresses the critical challenge of poor visibility in aquatic environments by integrating image enhancement methods with deep learning architectures. This work has significant implications for oceanographic mapping, environmental monitoring, and underwater archaeology, enabling AUVs to autonomously detect and classify objects in murky waters. By bridging the gap between image preprocessing and robust neural network models, Tarekegn’s research improves the reliability of underwater robotic systems. His contributions are particularly valuable for real-world applications where traditional computer vision fails, positioning him as an emerging voice in the intersection of marine robotics and artificial intelligence.