香蕉叶片病害检测与分类方法的比较分析

N. B. Raja, P. Selvi Rajendran
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引用次数: 2

摘要

毫无疑问,农业及其相关产业是印度最大的收入来源。植物病害是当今农业的一个主要问题,因为它会降低粮食产量和质量。先前感染的植物疾病、微生物、真菌、蛔虫和营养缺乏对作物造成重大损害,并造成以下后果:作物产量和质量下降。它还会杀死植物,减少农民的利润,并在整个控制期内提高生产成本。香蕉是太平洋和亚洲最重要的水果。香蕉植物易受几种疾病的影响,其影响可以从叶子上看到。感染将是条纹病毒,黄色Sigatoka,巴拿马,黑色Sigatoka和香蕉束顶病毒。因此,及早发现植物病害是很重要的。这些研究主要集中在深度学习算法上。本研究为研究香蕉病害检测的完整背景做出了巨大的潜在努力。最后,本研究还重点比较了各种分类方法在香蕉叶病害检测方面的最新研究方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparative Analysis of Banana Leaf Disease Detection and Classification Methods
Agriculture, along with its related industries, is without a doubt India’s largest source of income. Plant disease is a major concern in agriculture today, as it decreases food production and quality. Plant diseases, that are previously infected, microbes, fungus, roundworms, and nutrient deficiency, inflict significant damage to crops and have the following consequences: lower crop yield and quality. It also kills the plant, reduces the farmer’s profits, and raises the cost of production throughout the control period. The banana is the most important fruit in Pacific and the Asia. The banana plant was susceptible to several ailments, the effects of that can be seen on the leaves. The infections would be Streak Virus, yellow Sigatoka, Panama, Black Sigatoka, and Banana Bunchy Top Virus. As a result, early detection of plant diseases is important. These researches greatly focus on Deep learning algorithms. In this study, huge potential efforts are made to study the complete background of banana disease detection. In the end, this study also highlights a comparison of recent research directions in banana leaf disease detection using various classification methods.
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