Deep Neural Network for Plant Disease Recognition

Authors: Sulekha Vasant Shardul, Ashwini Vijay Waje

Country: India

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Abstract: Plant infections can devastatingly affect crops, prompting critical monetary misfortunes and food uncertainty. Early location and characterization of plant infections are critical for powerful administration and counteraction. This paper proposes a profound learning-based approach for plant infection grouping and location utilizing Convolutional Brain Organizations (CNNs) and move learning. We utilize pre-prepared CNN models and tweak them on a dataset of plant pictures with different sicknesses. Our outcomes show that the exchange learning approach accomplishes high exactness (95.6%) in arranging plant illnesses, beating conventional AI techniques. We additionally explore the utilization of information increase and move figuring out how to conquer the issue of restricted dataset size. The proposed framework can possibly help ranchers, scientists, and policymakers in checking and overseeing plant sicknesses, at last further developing harvest yields and food security.

Keywords: Plant disease classification, Deep learning, Convolutional Neural Networks (CNNs), Transfer learning.

Paper Id: 232742

Published On: 2025-10-02

Published In: Volume 13, Issue 5, September-October 2025

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