Real-time jute leaf disease classification using an explainable lightweight CNN via a supervised and semi-supervised self-training approach

These results highlight the novelty of combining SSL with a lightweight CNN to deliver near-supervised performance, improved interpretability, and real-world applicability while substantially reducing the dependence on expert-labeled data.

Authors

Mohammad Asif Hasan (ORCID: https://orcid.org/0000-0003-1342-434X)
Muhammad E. H. Chowdhury (ORCID: https://orcid.org/0000-0003-0744-8206)
Md. Zehan Alam (ORCID: https://orcid.org/0000-0003-3145-901X)
Avijit Paul
Md Shahab Uddin
M Jannat

Institutions

Chittagong University of Engineering & Technology (BD)
Manchester Metropolitan University (GB)
Maharishi International University (US)
Rajshahi University of Engineering and Technology (BD)
Qatar University (QA)
University of Rajshahi (BD)

Publication Details

Journal: Frontiers in Plant Science
Published: 2025-10-24
DOI: https://doi.org/10.3389/fpls.2025.1647177
Primary Topic: Smart Agriculture and AI
Type: article
Field-Weighted Citation Impact: 0.00

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article

Real-time jute leaf disease classification using an explainable lightweight CNN via a supervised and semi-supervised self-training approach

Mohammad Asif Hasan, Muhammad E. H. Chowdhury, Md. Zehan Alam, Avijit Paul et al.

Oct 24, 2025

Frontiers in Plant Science

Smart Agriculture and AI

article

Real-time jute leaf disease classification using an explainable lightweight CNN via a supervised and semi-supervised self-training approach

Mohammad Asif Hasan, Muhammad E. H. Chowdhury, Md. Zehan Alam, Avijit Paul, Md Shahab Uddin, M Jannat

October 24, 2025article en

Abstract

These results highlight the novelty of combining SSL with a lightweight CNN to deliver near-supervised performance, improved interpretability, and real-world applicability while substantially reducing the dependence on expert-labeled data.

Frontiers in Plant ScienceVol. 16

Chittagong University of Engineering & Technology (BD), Manchester Metropolitan University (GB), Maharishi International University (US), Rajshahi University of Engineering and Technology (BD), Qatar University (QA), University of Rajshahi (BD)

Openalex Percentile: Top 78%

Smart Agriculture and AI

DOI Open Access PDF OpenAlex

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Real-time jute leaf disease classification using an explainable lightweight CNN via a supervised and semi-supervised self-training approach — Mohammad Asif Hasan, Muhammad E. H. Chowdhury, et al. · Frontiers in Plant Science (2025) | TGRS Research Map | TGRS