Plant Leaf Disease Recognition Using Machine Learning

Abstract

Abstract— Plant leaf diseases significantly impact agricultural productivity, leading to substantial crop losses if not detected early. This paper introduces a deep learning approach for automatically identifying and classifying potato leaf diseases using image data. By utilizing transfer learning with MobileNetV2, a lightweight yet efficient CNN, the system accurately distinguishes between Early Blight, Late Blight, and Healthy leaves. The process includes dataset collection, preprocessing, model training, and real-time web application deployment for user interaction. Experimental results highlight high prediction accuracy and practical feasibility, making this system a valuable asset for precision agriculture and crop protection. Keywords— Plant leaf Disease Detection, Convolutional Neural Networks (CNNs), Image Classification, Transfer Learning, MobileNetV2, Image Preprocessing, Crop Protection, Deep Learning.

Plant phenotyping relevance

ジャガイモ葉の病害状態を画像から分類する深層学習手法が研究の中心であり、植物病害表現型の取得・推定に該当する。

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