Muhammad Faris Bin Kamarudzaman

University of Yamanashi

Papers

1

Total Citations

3

H-Index

1

About

Muhammad Faris Bin Kamarudzaman is a researcher at the forefront of agricultural robotics and artificial intelligence, with a focused expertise in precision viticulture and automated crop management. His work addresses the critical challenge of labor-intensive tasks in modern agriculture, particularly grape thinning—a selective process essential for improving fruit quality. In his most cited paper, "Automating Grape Thinning: Predicting Robotic Arm End-effector Positions Using Depth Sensing Technology and Neural Networks" (2023), Kamarudzaman pioneered a novel integration of depth sensing and neural networks to enable robotic arms to autonomously identify and target grape clusters. This contribution has garnered 3 citations, establishing a foundation for reducing labor costs and increasing efficiency in vineyards. His research bridges the gap between computer vision, robotics, and agronomy, offering scalable solutions for sustainable farming. By leveraging deep learning for real-time spatial prediction, Kamarudzaman’s work not only advances automation in viticulture but also sets a precedent for applying AI to other precision agriculture tasks. His innovative approach underscores a commitment to transforming traditional farming through technology, making him a notable figure in the emerging field of smart agriculture.

Research Focus

Key Achievements

1
H-Index
1
Papers
3
Total Citations
3
Avg Citations/Paper
🏆 Most Cited Paper
Automating Grape Thinning: Predicting Robotic Arm End-effector Positions Using Depth Sensing Technology and Neural Networks
3 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: University of Yamanashi

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago