畜牧与兽医2026，Vol.58Issue(9)：145-149,5.
基于人工智能的工作犬行为性状识别系统及其评价分析方法与应用前景
An AI-based working dog behavioral trait recognition system:evaluation methods and application prospects research
摘要
Abstract
Working dogs are widely employed in scenarios such as search and rescue,riot control,guide assistance,and herding.Their performance is composed of a series of canine behaviors,making the evaluation of these behaviors a critical basis for cultivating and measur-ing their working capabilities.Traditional methods for assessing working dog behavior rely heavily on human subjective experience,which of-ten leads to issues such as fragmented data collection,ambiguous evaluation criteria,and poor reproducibility.In recent years,artificial in-telligence has been increasingly adopted as an electronic refereeing system in various sports competitions.It demonstrates objectivity and pre-cision in analyzing athletic behaviors and offers a novel approach to evaluating working dog behavior.By incorporating Artificial Intelligence(AI),comprehensive and automated data collection on working dog behavior can be achieved,while deep learning algorithms enable accu-rate recognition and prediction of behavioral patterns.This not only effectively mitigates evaluation biases caused by human factors but also significantly enhances evaluation efficiency and repeatability,providing scientific and reliable technical support for selection,training,and competency assessment of working dogs.Therefore,this review is to examine how AI empowers the evaluation of working dog behavior,pro-moting a shift toward data-driven,precise,and efficient intelligent transformation in working dog training and service applications,thereby offering both technical support and theoretical reference for advancing the overall service capacity of the working dog industry.关键词
人工智能/工作犬/行为评价/数据采集Key words
artificial intelligence/working dogs/behavioral evaluation/data collection分类
农业科技引用本文复制引用
张刘睿祺,陶晓冉,朱靖,陈龙,蒿阳,黄建平..基于人工智能的工作犬行为性状识别系统及其评价分析方法与应用前景[J].畜牧与兽医,2026,58(9):145-149,5.基金项目
科技强警基础工作专项(2023JC12) （2023JC12）
