Ahmed Fareed Japar

Universiti Putra Malaysia

Papers

2

Total Citations

16

H-Index

2

About

Ahmed Fareed Japar is a researcher at the forefront of agricultural automation, specializing in computer vision and robotics for palm oil plantation management. His work directly addresses the critical challenge of loose fruit collection—a process that accounts for the majority of palm oil extraction profits. Japar’s most significant contribution is his pioneering application of the YOLOv4 object detection algorithm for real-time loose fruit identification, as demonstrated in his highly cited 2024 study (14 citations). This research lays the groundwork for autonomous mobile robot collectors, leveraging high-resolution 4K and 1080p video data to overcome the complexities of varied plantation environments. His earlier foundational work (2022) systematically investigated existing loose fruit collection technologies, establishing the operational and economic necessity for automated solutions. By bridging the gap between deep learning and agricultural robotics, Japar is driving a paradigm shift toward precision farming in the palm oil industry. His research not only promises to reduce labor dependency and operational costs but also enhances yield efficiency, positioning him as a key innovator in smart agriculture and field robotics.

Research Focus

Key Achievements

2
H-Index
2
Papers
16
Total Citations
8
Avg Citations/Paper
🏆 Most Cited Paper
Oil Palm Loose Fruit Detection Using YOLOv4 for an Autonomous Mobile Robot Collector
14 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: Universiti Putra Malaysia

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago