K M Abubeker

About

K M Abubeker is a researcher at the forefront of applying computer vision to agricultural automation. His primary research focus lies in developing deep learning-based object detection systems for precision agriculture, with a particular emphasis on the classification and quality assessment of horticultural produce. Abubeker’s major contribution is the pioneering application of the YOLO V5 framework to the real-time classification of bird eye chili (also known as 'kantahri mulaku'). His 2023 paper, "Computer Vision Assisted Real-Time Bird Eye Chili Classification Using YOLO V5 Framework," has garnered 9 citations, demonstrating its relevance in the emerging field of AI-driven agriculture. In this work, he proposed a robust classification model capable of distinguishing chili grades with high accuracy, addressing a critical need for automated post-harvest processing. A follow-up study, "Computer Vision Assisted Bird–Eye Chilli Classification Framework Using YOLO V5 Object Detection Model," further refined the methodology. Abubeker’s work is notable for bridging the gap between state-of-the-art object detection algorithms and practical agricultural challenges, offering scalable solutions that can reduce manual labor and improve supply chain efficiency. His research holds significant promise for smallholder farmers and the broader agri-tech industry.

Research Focus

Key Achievements

Top Papers

1. 1
   Computer Vision Assisted Real-Time Bird Eye Chili Classification Using YOLO V5 Framework

   9 citations · 2023
2. 2
   Computer Vision Assisted Bird–Eye Chilli Classification Framework Using YOLO V5 Object Detection Model

   2 citations · 2023

Key Collaborators

Contact & Links