首页|From beasts to bytes:Revolutionizing zoological research with artificial intelligence

From beasts to bytes:Revolutionizing zoological research with artificial intelligence

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  • 国家科技期刊平台
  • NETL
  • NSTL
  • 万方数据
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 Al 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 Al into this field.Based on numerous case studies,this review outlines various avenues for incorporating Al 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 Al applications in zoological research that have not yet been explored.

Animal scienceData extractionClassification modelBehavior analysisBiomolecular sequences analysis

Yu-Juan Zhang、Zeyu Luo、Yawen Sun、Junhao Liu、Zongqing Chen

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Chongqing Key Laboratory of Vector Insects

Chongqing Key Laboratory of Animal Biology

College of Life Science,Chongqing Normal University,Chongqing 401331,China

School of Mathematical Sciences,Chongqing Normal University,Chongqing 401331,China

Chongqing National Center for Applied Mathematics,Chongqing Normal University,Chongqing 401331,China

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National Natural Science Foundation of ChinaNatural Science Foundation of Chongqing,ChinaScience and Technology Research Program of Chongqing Municipal Education CommissionTeam Project of Innovation Leading Talent in Chongqing"Contract System"Project of Chongqing Talent Plan

31871274CSTB2022NSCQ-MSX0650KJQN202100508CQYC20210309536cstc2022ycjhbgzxm0147

2023

10.24272/j.issn.2095-8137.2023.263

动物学研究
中国科学院昆明动物研究所 中国动物学会

动物学研究

CSTPCDCSCD
影响因子：0.582
ISSN：0254-5853
年,卷(期)：2023.44(6)
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