House Plant Leaf Disease Detection and Classification Using Machine Learning

B. Usharani
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Abstract

Hibiscus is a fantastic herb, and in Ayurveda, it is one of the most renowned herbs that have extraordinary healing properties. Hibiscus is rich in vitamin C, flavonoids, amino acids, mucilage fiber, moisture content, and antioxidants. Hibiscus can help with weight loss, cancer treatment, bacterial infections, fever, high blood pressure, lower body temperature, treat heart and nerve diseases. Automatic leaf disease detection is an essential task. Image processing is one of the popular techniques for the plant leaf disease detection and categorization. In this chapter, the diseased leaf is identified by concurrent k-means clustering algorithm and then features are extracted. Finally, reweighted KNN linear classification algorithms have been used to detect the diseased leaves categories.
基于机器学习的室内植物叶片病害检测与分类
木槿是一种神奇的草药,在阿育吠陀,它是最著名的草药之一,具有非凡的治疗特性。木槿富含维生素C、类黄酮、氨基酸、粘液纤维、水分和抗氧化剂。木槿可以帮助减肥,治疗癌症,细菌感染,发烧,高血压,降低体温,治疗心脏和神经疾病。叶片病害自动检测是一项必不可少的任务。图像处理是植物叶片病害检测与分类的常用技术之一。在本章中,采用并发k-means聚类算法对病叶进行识别,并提取特征。最后,利用加权KNN线性分类算法检测病害叶片类别。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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