利用机器学习技术进行大豆作物病害分类

2020 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER) Pub Date : 2020-10-30 DOI:10.1109/DISCOVER50404.2020.9278060

R. Krishna, P. V.

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引用次数: 5

摘要

机器学习在分类和回归等许多应用中被广泛使用。利用机器学习技术对大豆作物病害进行分类。农作物的物理特性和天气参数被用作分类的属性。采用K近邻、朴素贝叶斯、决策树、神经网络等算法进行分类。结果与称为bagging的集成分类器进行了比较。

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Soybean crop disease classification using machine learning techniques

Machine learning is very widely used for many applications like classification and regression. Diseases in the soybean crop are classified using machine learning techniques. Physic crop properties and weather parameters are used as a attributes for classification. K nearest neighbor, naive Bayes, decision tree, neural network algorithms are used for classification. The result is compared with the ensemble classifier called bagging.

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2020 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER)

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