A Survey on Machine Learning in Agriculture - background work for an unmanned coconut tree harvester

Sakthiprasad K. M., R. K. Megalingam
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引用次数: 7

Abstract

Agriculture of a country must increase with the population otherwise that would affect the economy. When the population increases the resource availability for agriculture gets reduces, so efficient methodologies are required in the field of agriculture to get maximum production from the limited resources. Precision agriculture is the solution for that, it is achieved by advanced technologies like wireless sensor networks, machine learning etc. Different machine learning algorithms are using to achieve precision agriculture like crop selection, to identify management zones, crop monitoring and phenology, climate estimation and plant disease diagnosis etc. Awareness about the machine learning technologies used in the agriculture field is helpful to make the learning algorithm for the autonomous coconut harvester.
农业机器学习研究综述——无人椰子树收割机的背景工作
一个国家的农业必须随着人口的增长而增长,否则就会影响到经济。当人口增加时,农业资源的可用性会减少,因此在农业领域需要有效的方法来从有限的资源中获得最大的产量。精准农业是解决这个问题的办法,它是通过无线传感器网络、机器学习等先进技术实现的。不同的机器学习算法被用于实现精准农业,如作物选择、确定管理区域、作物监测和物候、气候估计和植物疾病诊断等。了解机器学习技术在农业领域的应用有助于自主椰子收获机的学习算法。
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