Mohamad Haniff Junos
Papers
1
Total Citations
15
H-Index
1
About
Mohamad Haniff Junos is a researcher whose work sits at the intersection of computer vision and environmental sustainability. His primary research focuses on developing deep learning models for automated waste detection and classification, a critical area for smart city infrastructure and recycling efficiency. His most-cited paper, "An automatic garbage detection using optimized YOLO model" (2023, 15 citations), demonstrates his expertise in optimizing state-of-the-art object detection architectures for real-world, resource-constrained applications. By refining the YOLO framework, Junos has contributed to making automated waste sorting more accurate and computationally efficient, addressing a pressing global challenge. His work not only advances the field of computer vision but also provides a tangible tool for improving waste management systems, highlighting his ability to bridge algorithmic innovation with practical, environmental impact.
Research Focus
Key Achievements
Top Papers
- 1An automatic garbage detection using optimized YOLO model15 citations · 2023