基于深度学习的柑橘叶片疾病分类

P. Sudharshan Duth, Shreeharsha Gopalkrishna Bhat
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引用次数: 2

摘要

印度是一个农业国家。它的经济主要以农作物生产为基础。为了保持印度在全球市场上的竞争优势,需要不断改善印度的农业部门。正是通过适当的监测,作物才健康无病。找到最有效和最合适的方法是非常具有挑战性和耗时的。通常,找到正确的需要专家和机器视觉系统等设备的帮助。在本研究中,深度学习是一种很有前途的模式识别技术,对五种不同的叶片病害进行了详细的研究。利用各种神经网络对柑桔叶片病害进行检测和分类,并得出比较结果,为本研究提供了解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Disease Classification in Citrus Leaf using Deep Learning
India is an agricultural country. Its economy is largely based on crop production. The continuous improvement of India’s agriculture sector is required to maintain its competitive advantage in the global market. It is through proper monitoring that the crop is healthy and disease-free. Finding the most effective and appropriate one can be very challenging and time-consuming. Usually, finding the right one requires the help of experts and equipment such as Machine Vision Systems. Deep learning is a promising technology for pattern recognition in this research work, a detailed study of five different leaf diseases. They are Blackspot, Canker, Miner, and Healthy leaves are used for the detection and classification of citrus leaf diseases using various neural networks and a comparative outcome is the solution of this work.
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