植物叶片病害检测使用图像处理和机器学习技术

IF 0.3
Pratibha Kokardekar, Aman Shah, Arjun Thakur, Prachi Shahu, Rohan Raggad, Sudhanshu Keshaowar, Vineet Pashine
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引用次数: 1

摘要

农业在加强一个国家的经济方面起着非常重要的作用。植物病害是造成生产和经济损失的主要原因,也降低了农产品的质量和数量。传统的、最常用的方法是用肉眼检测疾病,但在检测过程中存在很大的困难。农作物病害检测是一项重要而又繁琐的工作。它需要大量的熟练劳动力和大量的时间。本文比较了现有疾病检测技术的优点和局限性。最后,本文将讨论一种利用卷积神经网络(CNN)检测植物病害的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Plant leaves disease detection using Image Processing and Machine learning techniques
Agriculture plays a very important role in strengthening the economy of a country. Disease in plants is the majorcause of production and economy loss which also reduced the quality and quantity of agriculture products. Farmersface a lot of difficulty in detecting the diseases with naked eye which is the traditional and most used way. It isan important and tedious task to detect disease on crops. It requires a lot of skilled labour and huge amount oftime. This paper compares the benefits and limitations of existing techniques for disease detections. Finally, itwill talk about a method for disease detection in plants using convolutional neural network (CNN).
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来源期刊
International Journal of Next-Generation Computing
International Journal of Next-Generation Computing COMPUTER SCIENCE, THEORY & METHODS-
自引率
66.70%
发文量
60
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