International Research Journal of Innovations in Engineering and Technology - IRJIET International Open Access, Monthly, Peer Reviewed, Reputed Journal ISSN (online): 2581-3048

Impact Factor (2025): 6.9

DOI Prefix: 10.47001/IRJIET

Deep Learning Techniques for Plant Disease Detection: A Comprehensive Review

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.

Country : India

1 Pijush Kanti Kumar

  1. Department of Information Technology, Government College of Engineering & Textile Technology, Serampore, Calcutta, India

IRJIET, Volume 8, Issue 7, July 2024 pp. 128-138

doi.org/10.47001/IRJIET/2024.807013

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