Neem Leaf Disease Detection Using Hybrid Deep Learning Models

Jaldu Balasubramanyam Guptha, E. Elakiya, K. Ramesh, E. Anuja

2025

Abstract

Neem is well-known for its medicinal value however; neem yields are highly affected by various leaf diseases. Management and control of the diseases requires timely and accurate detection. This paper introduces a mobile hybrid deep learning framework based on MobileNet and DenseNet that has high accuracy of 90.5% compared to other hybrid models. The proposed framework consists of image processing, feature extraction model, and ensemble learning model to improve accuracy and robustness. The dataset includes 1862 images of neem leaf diseases in six classes; a split of an 80-20 training to testing ratio was used for the dataset. The proposed MobileNet DenseNet framework is an enhancement from existing framework and illustrates the feature extraction and classification capabilities. Empirical results support our model has the highest accuracy and is an effective approach for neem leaf disease detection. The current paper provides precision agriculture with an automated framework for accurate neem leaf disease detection and timely disease management programs.

Paper Citation

in Harvard Style

Guptha J., Elakiya E., Ramesh K. and Anuja E. (2025). Neem Leaf Disease Detection Using Hybrid Deep Learning Models. In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25; ISBN 978-989-758-777-1, SciTePress, pages 627-635. DOI: 10.5220/0013887500004919

in Bibtex Style

@conference{icrdicct`2525,
author={Jaldu Guptha and E. Elakiya and K. Ramesh and E. Anuja},
title={Neem Leaf Disease Detection Using Hybrid Deep Learning Models},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25},
year={2025},
pages={627-635},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013887500004919},
isbn={978-989-758-777-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25
TI - Neem Leaf Disease Detection Using Hybrid Deep Learning Models
SN - 978-989-758-777-1
AU - Guptha J.
AU - Elakiya E.
AU - Ramesh K.
AU - Anuja E.
PY - 2025
SP - 627
EP - 635
DO - 10.5220/0013887500004919
PB - SciTePress