Nur Athirah Zailan
Papers
3
Total Citations
61
H-Index
3
About
Nur Athirah Zailan is a researcher at the forefront of applying deep learning to environmental monitoring, with a specialized focus on automated waste detection in riverine ecosystems. Her work addresses the critical challenge of urban solid waste pollution threatening water quality and ecological health. Zailan’s major contribution lies in optimizing the YOLO (You Only Look Once) object detection model for real-time, automated identification of floating debris and solid waste in rivers. Her most cited paper, "An automated solid waste detection using the optimized YOLO model for riverine management" (2022, 42 citations), demonstrates a practical AI solution for urban riverine management, enabling efficient monitoring and mitigation of pollution sources. She further refined this approach in "An automatic garbage detection using optimized YOLO model" (2023, 15 citations) and explored network fusion techniques in "YOLO-based Network Fusion for Riverine Floating Debris Monitoring System" (2021). Collectively, her work has garnered over 60 citations, highlighting its relevance for environmental engineers, urban planners, and conservationists seeking scalable, technology-driven solutions to combat riverine litter and protect aquatic ecosystems.
Research Focus
Key Achievements
Top Papers
- 1
- 2An automatic garbage detection using optimized YOLO model15 citations · 2023
- 3YOLO-based Network Fusion for Riverine Floating Debris Monitoring System4 citations · 2021