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DOI Prefix: 10.47001/IRJIET

Deep Learning Techniques for Plant Disease Detection: A Comprehensive Review

Pijush Kanti KumarDepartment of Information Technology, Government College of Engineering & Textile Technology, Serampore, Calcutta, India

Vol 8 No 7 (2024): Volume 8, Issue 7, July 2024 | Pages: 128-138

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 27-07-2024

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Abstract

The advancement of deep learning techniques has revolutionized the field of computer vision and enabled the development of sophisticated systems for plant disease detection. This review paper explores the state-of-the-art deep learning methodologies and their applications in the context of plant disease detection [1]. We analyze the evolution of this field, from data collection and preprocessing to model selection, transfer learning, and deployment. Additionally, we discuss the challenges, achievements, and future directions of deep learning-based plant disease detection systems [2], aiming to provide a comprehensive overview for researchers, practitioners, and policymakers in the agriculture sector.

Keywords

Plant disease detection, Deep learning, Convolutional neural networks, Transfer learning, Agriculture


Citation of this Article

Pijush Kanti Kumar. (2024). Deep Learning Techniques for Plant Disease Detection: A Comprehensive Review. International Research Journal of Innovations in Engineering and Technology - IRJIET, 8(7), 128-138, Article DOI https://doi.org/10.47001/IRJIET/2024.807013

Licence Copyright (c) 2026 International Research Journal of Innovations in Engineering and Technology creative common licence This work is licensed under Creative common Attribution Non Commercial 4.0 Internation Licence
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