Mustafa Sameer
Papers
1
Total Citations
3
H-Index
1
About
Mustafa Sameer is a rising researcher in computer vision, with a focused expertise in real-time object detection and its applications in autonomous systems. His most-cited work, "Real-Time Vehicle Detection using YOLOv8 and Data Augmentation Approach," demonstrates a practical, high-impact contribution to the field. In this study, Sameer leverages the cutting-edge YOLOv8 architecture, a leading framework in the You Only Look Once (YOLO) family, and enhances its robustness through data augmentation techniques. This approach directly addresses critical challenges in autonomous driving, surveillance, and robotics—enabling faster, more accurate vehicle detection under varied real-world conditions. With 3 citations already for this 2023 paper, his work is gaining traction among practitioners and researchers seeking efficient, deployable solutions. Sameer’s contributions stand out for bridging state-of-the-art model performance with practical data strategies, making his research a valuable reference for those advancing real-time computer vision systems. His trajectory signals a promising career at the intersection of deep learning and applied perception.
Research Focus
Key Achievements
Top Papers
- 1Real-Time Vehicle Detection using YOLOv8 and Data Augmentation Approach3 citations · 2023