An explainable deep learning-based framework for multi-class potato leaf disease detection using real-world field images collected from agricultural environments in Bangladesh is proposed and aims to enhance diagnosis accuracy, reduce crop losses, minimize unnecessary pesticide use, and promote smart farming practices.
Early identification of plant diseases is crucial for maintaining agricultural productivity and ensuring food security. Manually inspecting crop leaves takes a lot of time and requires expertise, making automated disease detection systems very helpful. This paper presents a framework for detecting leaf diseases in mult...
B. Likitha· International Journal of Dru...· 0 citations
A comprehensive and systematic review of state-of-the-art methods for detecting potato leaf disease, covering convolutional neural networks, transformer-based architectures, and hybrid models, and a strategic comparative analysis is conducted.
Potato cultivation is crucial to global agriculture, but continues to face challenges from various disturbances, including six classes of potato diseases: pests, nematodes, viruses, fungi, Phytophthora, and bacteria. These diseases can spread rapidly across fields, causing potato shortages, resulting in significant los...
Marvin Octavianus Salim Purnama, Geraldan Ahmad Hafizh, Nicholas Tirta et al.· International Conferences on...· 0 citations
Early and precise diagnosis of maize leaf diseases is vital to reduce crop losses and to ensure sustainable farming production. Nevertheless, traditional Deep Learning models are usually “black boxes,” making them unreliable and unpopular in real-world agricultural decision-making processes. To provide transparent and...
K. S. Kumar, Raveendrababu Vempati, J. Rahul· 2026 6th International Confe...· 0 citations
A lightweight, effectual CNN model trained from scratch for classifying apple leaf images into four categories: healthy, rust, scab, and multiple diseases achieves good classification performance while maintaining a simple architecture suitable for identifying apple leaf diseases in the context of precision agriculture...
V. Devi, Pardeep Kumar· International Journal of Com...· 0 citations
Diseases affecting crops threaten farmers incomes, food security, and agricultural production. Traditional methods for detecting diseases rely on consultation with professionals, as well as inspections made by a person, and are often quite labor-intensive. In this paper, the system that uses artificial intelligence (AI...
Yasir Abdullah Rabi Ahamed, Lakshmana Kumar T, V. M et al.· International Conference Inn...· 0 citations
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