Efficient Detection of Cucurbit Pepo Leaf Diseases Using Advanced Image Processing Techniques

P. A. Selvaraj, K. Dhanushree, G. K. Ranga Kaarthi, R. K. Sanjith

2025

Abstract

Curcurbita pepo leaf diseases are among the critical factors that bring down agricultural productivity and, therefore, require an accurate diagnostic tool. In this paper, there has been proposed a classification model for recognizing four common diseases of Cucurbita pepo leaf—Downy Mildew, Powdery Mildew, Mosaic Disease, and Bacterial Leaf Spot—together with healthy leaves using YOLOv7 and Convolutional Neural Networks. In this paper, the authors use the Cucurbita pepo leaf disease dataset, which includes 2000 high resolution images, to correctly classify a given leaf as healthy or infected. The dataset is well structured and will enhance studies investigating disease symptoms, becoming very useful in agricultural studies and education. Our findings demonstrate how state-of-the-art computer vision models could be put into practice to improve disease diagnosis for the promotion of precision agriculture and automated systems for real-time monitoring of diseases at the point of intervention. Therefore, such technologies will help the agricultural sector realize efficient management of diseases since reduced losses will result in higher quality yields. This research highlights the realization of incorporating artificial intelligence and machine learning in farming processes to minimize challenges and improve productivity.

Paper Citation

in Harvard Style

Selvaraj P., Dhanushree K., Kaarthi G. and Sanjith R. (2025). Efficient Detection of Cucurbit Pepo Leaf Diseases Using Advanced Image Processing Techniques. In Proceedings of the 3rd International Conference on Futuristic Technology - Volume 3: INCOFT; ISBN 978-989-758-763-4, SciTePress, pages 470-475. DOI: 10.5220/0013622000004664

in Bibtex Style

@conference{incoft25,
author={P. A. Selvaraj and K. Dhanushree and G. K. Ranga Kaarthi and R. K. Sanjith},
title={Efficient Detection of Cucurbit Pepo Leaf Diseases Using Advanced Image Processing Techniques},
booktitle={Proceedings of the 3rd International Conference on Futuristic Technology - Volume 3: INCOFT},
year={2025},
pages={470-475},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013622000004664},
isbn={978-989-758-763-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Futuristic Technology - Volume 3: INCOFT
TI - Efficient Detection of Cucurbit Pepo Leaf Diseases Using Advanced Image Processing Techniques
SN - 978-989-758-763-4
AU - Selvaraj P.
AU - Dhanushree K.
AU - Kaarthi G.
AU - Sanjith R.
PY - 2025
SP - 470
EP - 475
DO - 10.5220/0013622000004664
PB - SciTePress