中国农业科技导报2024，Vol.26Issue(10)：110-124,15.DOI:10.13304/j.nykjdb.2023.0168
深度学习在畜禽典型行为识别中的研究进展
Research Progress of Deep Learning in Typical Behavior Recognition of Livestock and Poultry
摘要
Abstract
The typical behaviors,such as feeding,drinking,standing and fighting,are closely related to the production capacity,health status as well as welfare of livestock and poultry,which affecting the production and economic benefits of livestock and poultry in farms.In fact,the traditional manual observation of livestock and poultry is not only time-consuming and laborious,but also highly subjective.So currently,the trend of large-scale livestock and poultry farming is accelerating.With the rapid development of machine learning as well as continuous optimization of neural networks,algorithms and computility,technologies such as computer vision,speech recognition,biometric recognition and natural language processing can accurately and efficiently monitor the information of livestock and poultry as well as analyze the physiological and health status of livestock and poultry,showing broad application prospects in the field of livestock and poultry.This article introduced the development history of deep learning technology,and then expounded the research progress of deep learning technology in behavior recognition of common livestock and poultry species such as cattle,pig,sheep and chicken,providing technical reference for future researches and practical applications.Meanwhile,this article summarized the problems and improvement strategies of deep learning technology in behavior recognition of common livestock and poultry from aspects of model versatility,data set diversity as well as the comprehensiveness of digital behavior results,aiming to provide theoretical reference for technicians to promote the further development of deep learning in the application of typical behavior of livestock and poultry.关键词
畜禽/深度学习/行为识别Key words
livestock and poultry/deep learning/behavior recognition分类
农业科技引用本文复制引用
朱芷芫,王海峰,李斌,赵文文,朱君,贾楠,赵宇亮..深度学习在畜禽典型行为识别中的研究进展[J].中国农业科技导报,2024,26(10):110-124,15.基金项目
国家重点研发计划项目(2022YED1301103) （2022YED1301103）
山东重点研发项目(2022TZXD0014) （2022TZXD0014）
2023年北京市农林科学院院财政专项. （）
