Since the late 2010s,Artificial Intelligence(AI)including machine learning,boosted through deep learning,has boomed as a vital tool to leverage computer vision,natural language processing and speech recognition in rev...Since the late 2010s,Artificial Intelligence(AI)including machine learning,boosted through deep learning,has boomed as a vital tool to leverage computer vision,natural language processing and speech recognition in revolutionizing zoological research.This review provides an overview of the primary tasks,core models,datasets,and applications of AI in zoological research,including animal classification,resource conservation,behavior,development,genetics and evolution,breeding and health,disease models,and paleontology.Additionally,we explore the challenges and future directions of integrating AI into this field.Based on numerous case studies,this review outlines various avenues for incorporating AI into zoological research and underscores its potential to enhance our understanding of the intricate relationships that exist within the animal kingdom.As we build a bridge between beast and byte realms,this review serves as a resource for envisioning novel AI applications in zoological research that have not yet been explored.展开更多
基金supported by the National Natural Science Foundation of China (31871274)Natural Science Foundation of Chongqing,China (CSTB2022NSCQ-MSX0650)+2 种基金Science and Technology Research Program of Chongqing Municipal Education Commission (KJQN202100508)Team Project of Innovation Leading Talent in Chongqing (CQYC20210309536)“Contract System”Project of Chongqing Talent Plan (cstc2022ycjh-bgzxm0147)。
文摘Since the late 2010s,Artificial Intelligence(AI)including machine learning,boosted through deep learning,has boomed as a vital tool to leverage computer vision,natural language processing and speech recognition in revolutionizing zoological research.This review provides an overview of the primary tasks,core models,datasets,and applications of AI in zoological research,including animal classification,resource conservation,behavior,development,genetics and evolution,breeding and health,disease models,and paleontology.Additionally,we explore the challenges and future directions of integrating AI into this field.Based on numerous case studies,this review outlines various avenues for incorporating AI into zoological research and underscores its potential to enhance our understanding of the intricate relationships that exist within the animal kingdom.As we build a bridge between beast and byte realms,this review serves as a resource for envisioning novel AI applications in zoological research that have not yet been explored.
