A Review on Tomato Disease and Artificially Intelligent Cure

Sachin Sharma, V. Mishra, Ashendra K. Saxena
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Abstract

Formers are the initial pillar of any country's economy. In this era, the cleanshaven occurred red in the plants as it has been affected by a lot of diseases. Due to that the loss of money, time, manpower, and hard work of farmers. The vegetables that are affected by the disease can even harm human life. As we all know, how plants are important in our life. Plants are the only source of income for farmers. They play a big role in the economic growth of any country Nowadays leaf disease detection is the main concern issue all over the world. Manual identification of the disease is a big challenge. Thus, numerous research has been initiated to identify the disease automatically in this context, and new emerging technology such as machine learning (ML) has been used. It will help to improve the usage of time and enhance Accuracy. This will help to enhance the economy of any country. The disease can harm any plant's quality and production, which will lead the economic loss. Detection of disease in its early stages can reduce the loss of farmers and will help to enhance production. Most of the diseases in plants have the same symptoms, and we can notice them with our naked eye. But early detection of disease and proper ways of remedy more essential, and it will help to reduce the global food problem. This article targets to develop a ML approach for early discovery of disease as well as suggest the appropriate solutions.
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番茄病害及其人工智能防治研究进展
毕业生是任何国家经济的最初支柱。在这个时代,由于受到许多疾病的影响,植物的清洗发生了红色。由于这损失了金钱、时间、人力和农民的辛勤劳动。受这种疾病影响的蔬菜甚至会危害人的生命。我们都知道,植物在我们的生活中是多么重要。植物是农民唯一的收入来源。它们在任何一个国家的经济增长中都起着重要的作用,目前叶片病害检测是世界各国关注的主要问题。人工识别疾病是一个巨大的挑战。因此,许多研究已经开始在这种情况下自动识别疾病,并且已经使用了机器学习(ML)等新兴技术。这将有助于改善时间的利用,提高准确性。这将有助于提高任何国家的经济。病害可以危害任何植物的品质和产量,造成经济损失。在疾病的早期阶段发现疾病可以减少农民的损失,并有助于提高产量。植物的大多数疾病都有相同的症状,我们可以用肉眼观察到它们。但早期发现疾病和适当的治疗方法更为重要,这将有助于减少全球粮食问题。本文旨在开发一种用于疾病早期发现的机器学习方法,并提出适当的解决方案。
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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