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Plants Disease Identification and Classification Through Leaf Images: A Survey

机译:通过叶图像进行植物病害识别和分类的调查

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The symptoms of plant diseases are evident in different parts of a plant; however leaves are found to be the most commonly observed part for detecting an infection. Researchers have thus attempted to automate the process of plant disease detection and classification using leaf images. Several works utilized computer vision technologies effectively and contributed a lot in this domain. This manuscript summarizes the pros and cons of all such studies to throw light on various important research aspects. A discussion on commonly studied infections and research scenario in different phases of a disease detection system is presented. The performance of state-of-the-art techniques are analyzed to identify those that seem to work well across several crops or crop categories. Discovering a set of acceptable techniques, the manuscript highlights several points of consideration along with the future research directions. The survey would help researchers to gain understanding of computer vision applications in plant disease detection.
机译:植物病害的症状在植物的不同部位都很明显。然而,叶子是发现感染最常观察到的部分。因此,研究人员尝试使用叶图像自动进行植物病害检测和分类过程。一些作品有效地利用了计算机视觉技术,并在这一领域做出了很多贡献。该手稿总结了所有此类研究的利弊,以阐明各个重要的研究方面。讨论了疾病检测系统不同阶段的常用感染和研究方案。对最先进技术的性能进行了分析,以确定那些在几种作物或作物类别中似乎效果很好的技术。该手稿发现了一套可以接受的技术,重点介绍了一些要点以及未来的研究方向。该调查将有助于研究人员了解计算机视觉在植物病害检测中的应用。

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