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E-Agri Kit: Agricultural Aid using Deep Learning

机译:E-Agri套件:使用深度学习的农业援助

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This paper presents an agricultural aid application, developed and designed, to help farmers by utilizing Image Processing, Machine Learning and Deep Learning concepts. Our application provides features such as early detection of plant disease, implemented using various approaches. After evaluation, results showed that Convolutional Neural Network was performing better for plant disease detection with an accuracy of 97.94% at 20 epochs. It further helps the farmer to forecast the weather to decide the right time for agricultural activities like harvesting and plucking. To avoid reoccurrence of disease due to loss in soil minerals, a crop specific fertilizer calculator is incorporated which can calculate the amount of urea, diammonium phosphate and muriate of potash required for a given area. Since India is a multilingual country, the application has been designed to incorporate language translation in four languages: Marathi, Hindi, Punjabi and English.
机译:本文介绍了农业援助应用,开发和设计,以利用图像处理,机器学习和深度学习概念来帮助农民。 我们的应用提供了使用各种方法实施的植物疾病的早期检测等功能。 在评估之后,结果表明,卷积神经网络对植物疾病检测表现更好,精度为20时的精度为97.94%。 它进一步帮助农民预测天气来决定收获和采集等农业活动的正确时间。 为了避免由于土壤矿物质损失引起的疾病的再发产,致良好的肥料计算器是可以计算给定区域所需的尿素,磷酸铵和钾肥的量。 由于印度是一个多语种国家,该申请旨在融入四种语言的语言翻译:Marathi,Hindi,Punjabi和英语。

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