基于决策树的叶片病害检测与分类

B. Rajesh, M. V. Sai Vardhan, L. Sujihelen
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引用次数: 22

摘要

农业生产力很大程度上依赖于经济。植物病害在农业中扮演着重要的角色,因为植物病害是非常自然的,如果不加以照顾,将对植物造成严重后果,从而影响产品的质量、数量或生产力。及时准确地诊断叶片病害对防止生产力损失和农产品损失或减少具有重要作用。通过自动化技术检测植物疾病是有益的,因为它减少了对大型植物的监测工作,并在植物叶片出现疾病时很早就检测到疾病的迹象。更多的研究人员提出了叶片病害检测技术。现有系统的检测精度较低。该系统使用决策树对叶片病害进行识别和分类,与现有系统相比,在更短的时间内提高了检测精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Leaf Disease Detection and Classification by Decision Tree
Agricultural productivity is very dependent on the economy. Plant diseases play an important role in agriculture because plant diseases are very natural and failure to care will have serious consequences for plants and therefore affect the quality, quantity, or productivity of the product. Timely and accurate diagnosis of leaf diseases plays a major part in preventing loss in productivity and loss or reduction of agricultural products. Detection of plant diseases by automated techniques is beneficial because it reduces monitoring efforts on large plants and detects an indication of disease which occurs when they came on the leaves of plants very early. More researchers have proposed leaf disease detection techniques. The existing systems have less detection accuracy. This proposed system uses a decision tree to identify and classify leaf disease and increases its detection accuracy with less time compared with the existing system.
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