Detection of Pomelo in Overlapping Conditions Using Drones

Mahdaniar, Indrabayu

2025

Abstract

Detection of Pomelo on trees in overlapping conditions and the similarity of colors between fruits and leaves are the main challenges in the implementation of smart farming systems. This study aims to develop an automatic detection system of Pomelo using a drone with a computer vision approach based on the YOLOv11 algorithm combined with the CLAHE (Contrast Limited Adaptive Histogram Equalization) image contrast enhancement technique. The research methodology includes image data collection, pre-processing, data labeling, model training, and evaluation using mAP, precision and recall. The initial results showed that YOLOv11 provide suboptimal performance in the detection process, resulting in the result, precision: 92%, recall: 81%, mAP50: 90%, mAP50-95: 72%. After YOLOv11 is integrated with CLAHE, the performance has been improved, achieving precision: 92%, recall: 84%, mAP50: 95%, mAP50-95: 67%.

Paper Citation

in Harvard Style

Mahdaniar. and Indrabayu. (2025). Detection of Pomelo in Overlapping Conditions Using Drones. In Proceedings of the 1st International Conference on Research and Innovations in Information and Engineering Technology - Volume 1: RITECH; ISBN 978-989-758-784-9, SciTePress, pages 25-31. DOI: 10.5220/0014266900004928

in Bibtex Style

@conference{ritech25,
author={Mahdaniar and Indrabayu},
title={Detection of Pomelo in Overlapping Conditions Using Drones},
booktitle={Proceedings of the 1st International Conference on Research and Innovations in Information and Engineering Technology - Volume 1: RITECH},
year={2025},
pages={25-31},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0014266900004928},
isbn={978-989-758-784-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Innovations in Information and Engineering Technology - Volume 1: RITECH
TI - Detection of Pomelo in Overlapping Conditions Using Drones
SN - 978-989-758-784-9
AU - Mahdaniar.
AU - Indrabayu.
PY - 2025
SP - 25
EP - 31
DO - 10.5220/0014266900004928
PB - SciTePress