Coconut Palm Tree Counting on Drone Images with Deep Object Detection and Synthetic Training Data

Tobias Rohe, Barbara Böhm, Michael Kölle, Jonas Stein, Jonas Stein, Robert Müller, Claudia Linnhoff-Popien

2025

Abstract

Drones have revolutionized various domains, including agriculture. Recent advances in deep learning have propelled among other things object detection in computer vision. This study utilized YOLO, a real-time object detector, to identify and count coconut palm trees in Ghanaian farm drone footage. The farm presented has lost track of its trees due to different planting phases. While manual counting would be very tedious and error-prone, accurately determining the number of trees is crucial for efficient planning and management of agricultural processes, especially for optimizing yields and predicting production. We assessed YOLO for palm detection within a semi-automated framework, evaluated accuracy augmentations, and pondered its potential for farmers. Data was captured in September 2022 via drones. To optimize YOLO with scarce data, synthetic images were created for model training and validation. The YOLOv7 model, pretrained on the COCO dataset (excluding coconut palms), was adapted using tailored data. Trees from footage were repositioned on synthetic images, with testing on distinct authentic images. In our experiments, we adjusted hyperparameters, improving YOLO’s mean average precision (mAP). We also tested various altitudes to determine the best drone height. From an initial mAP@.5 of 0.65, we achieved 0.88, highlighting the value of synthetic images in agricultural scenarios.

Paper Citation

in Harvard Style

Rohe T., Böhm B., Kölle M., Stein J., Müller R. and Linnhoff-Popien C. (2025). Coconut Palm Tree Counting on Drone Images with Deep Object Detection and Synthetic Training Data. In Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-737-5, SciTePress, pages 662-669. DOI: 10.5220/0013172900003890

in Bibtex Style

@conference{icaart25,
author={Tobias Rohe and Barbara Böhm and Michael Kölle and Jonas Stein and Robert Müller and Claudia Linnhoff-Popien},
title={Coconut Palm Tree Counting on Drone Images with Deep Object Detection and Synthetic Training Data},
booktitle={Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2025},
pages={662-669},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013172900003890},
isbn={978-989-758-737-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - Coconut Palm Tree Counting on Drone Images with Deep Object Detection and Synthetic Training Data
SN - 978-989-758-737-5
AU - Rohe T.
AU - Böhm B.
AU - Kölle M.
AU - Stein J.
AU - Müller R.
AU - Linnhoff-Popien C.
PY - 2025
SP - 662
EP - 669
DO - 10.5220/0013172900003890
PB - SciTePress