Exploring Camouflaged Object Detection Techniques for Invasive Vegetation Monitoring

Henry Velesaca, Henry Velesaca, Hector Villegas, Angel Sappa, Angel Sappa

2025

Abstract

This paper presents a novel approach to weed detection by leveraging state-of-the-art camouflaged object detection techniques. The work evaluates six camouflaged object detection architectures on agricultural datasets to identify weeds naturally blending with crops through similar physical characteristics. The proposed approach shows excellent results in detecting weeds using Unmanned Aerial Vehicle images. This work establishes a new framework for the challenging task of weed detection in agricultural settings using camouflaged object detection approaches, contributing to more efficient and sustainable farming practices.

Paper Citation

in Harvard Style

Velesaca H., Villegas H. and Sappa A. (2025). Exploring Camouflaged Object Detection Techniques for Invasive Vegetation Monitoring. In Proceedings of the 14th International Conference on Data Science, Technology and Applications - Volume 1: DATA; ISBN 978-989-758-758-0, SciTePress, pages 619-626. DOI: 10.5220/0013630200003967

in Bibtex Style

@conference{data25,
author={Henry Velesaca and Hector Villegas and Angel Sappa},
title={Exploring Camouflaged Object Detection Techniques for Invasive Vegetation Monitoring},
booktitle={Proceedings of the 14th International Conference on Data Science, Technology and Applications - Volume 1: DATA},
year={2025},
pages={619-626},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013630200003967},
isbn={978-989-758-758-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Conference on Data Science, Technology and Applications - Volume 1: DATA
TI - Exploring Camouflaged Object Detection Techniques for Invasive Vegetation Monitoring
SN - 978-989-758-758-0
AU - Velesaca H.
AU - Villegas H.
AU - Sappa A.
PY - 2025
SP - 619
EP - 626
DO - 10.5220/0013630200003967
PB - SciTePress