Heliza Rahmania Hatta
Papers
2
Total Citations
73
H-Index
2
About
Heliza Rahmania Hatta is a researcher at the forefront of applying computer vision and image processing to agricultural challenges, particularly in the domain of precision farming and post-harvest technology. Her core research focuses on developing automated segmentation techniques to identify and analyze fruits, enabling critical applications such as maturity grading and robotic harvesting. Hatta’s most impactful contribution is her work on oil palm fruit segmentation, where she introduced a contour-based approach that achieved 57 citations, providing a robust method for automating the sorting of this economically vital crop. She has further advanced the field by integrating K-means clustering with edge detection for tomato segmentation, a study that has garnered 16 citations and demonstrates the versatility of her methods across different horticultural products. By bridging the gap between computational algorithms and real-world agricultural needs, Hatta’s research offers practical, scalable solutions for improving efficiency in food production. Her work is particularly notable for its direct application to plantation management, helping to reduce labor costs and increase accuracy in fruit quality assessment.
Research Focus
Key Achievements
Top Papers
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