Braja Manggala
Papers
1
Total Citations
3
H-Index
1
About
Braja Manggala is a researcher at the forefront of applying artificial intelligence to food safety and agricultural technology. His primary research focuses on developing intelligent computer vision systems for real-time quality control in food processing, with a particular emphasis on deep learning-based object detection. Manggala’s most notable contribution is the creation of an innovative inspection system utilizing the YOLOv7 framework to detect foreign materials in fresh-cut vegetables—a critical advancement for ensuring consumer health and product integrity. This work, published in 2025, has already garnered attention with 3 citations, demonstrating its early impact in the field. By addressing the persistent challenge of contaminants in minimally processed produce, Manggala’s research bridges the gap between state-of-the-art machine learning and practical industrial applications. His approach not only enhances food safety protocols but also offers scalable, real-time solutions that can be integrated into existing production lines. For students and researchers exploring the intersection of AI and food technology, Manggala’s work exemplifies how deep learning can transform traditional quality assurance processes into more efficient, accurate, and automated systems.
Research Focus
Key Achievements
Top Papers
- 1