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基于深度学习的农作物检测识别研究现状及展望

Research Status and Prospect of Crop Detection and Identification based on Deep Learning

  • 摘要: 深度学习是利用神经网络分析样本数据的内在特征和表达层次,学习具有多个抽象层次的数据表示的机器学习技术。本文概述了近年来深度学习技术在水果识别、农作物病害识别、农作物虫害识别、田间杂草识别、目标农作物定位等农作物检测识别领域内的研究进展,分析了目前深度学习技术存在的理论、建模、环境、成本及应用问题,提出了算法优化、应用多维化、处理效率与计算能力提升的发展趋势。

     

    Abstract: Deep learning is a machine learning technology that uses neural networks to analyze the inherent features and expression levels of sample data and learn data representations with multiple levels of abstraction.This paper summarizes the research progress of deep learning technology in the fields of fruit identification,crop disease identification,crop pest identification,field weed identification,target crop positioning and other crop detection and identification fields in recent years,and analyzes the existing deep learning technology,environment,cost and application issues,and put forward the development trend of algorithm optimization,application multi-dimensionality,processing efficiency and computing power improvement.

     

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