深度学习在农业病虫害智能识别方面的研究进展

Research Progress of Deep Learning in Intelligent Identification of Agricultural Diseases and Insect Pests

深度学习(Deep Learning,DL)附属于机器学习算法的一个分支,实质是一种通过海量数据对构建的多层隐藏层进行训练,使其习得一种更有意义的抽象特征,从而提高分类及预测准确性的算法,其是通过模拟人脑的深层神经结构来学习和表达文本、图像、声音和动作等数据。近些年来深度学习已经广泛应用于智慧农业各类病虫害。该文首先详细介绍深度学习,其次以深度学习在茶树病虫害智能识别方面的具体进展及研究为例进行介绍,最后在查阅相关文献的基础上讨论分析,得出进一步的结论。通过对相关研究的系统综述,以深度学习为基础深入探索农业病虫害智能识别的研究。

Deep Learning(DL),which is attached to a branch of machine learning algorithm,is essentially an algorithm that trains multi-layer hidden layers through massive data to acquire a more meaningful abstract feature,so as to improve the accuracy of classification and prediction.It learns and expresses text,image,sound and action data by simulating the deep neural structure of the human brain.In recent years,Deep Learning has been widely used in all kinds of diseases and insect pests in smart agriculture.This paper will introduce Deep Learning in detail,and then take the specific progress and research of Deep Learning in intelligent identification of tea diseases and insect pests as an example,and finally discuss and analyze it on the basis of consulting relevant literature,and draw further conclusions.Through a systematic review of related research,this paper explores the intelligent identification of agricultural diseases and insect pests on the basis of Deep Learning.