典型文献
Editorial for Special Issue on Brain-inspired Machine Learning
文献摘要：
The recent years have witnessed significant progress on artificial intelligence(AI).Undoubtedly,one of the es-sential elements that contribute to the prosperity of cur-rent AI is brain-inspired machine learning.By introdu-cing structural principles and operational mechanisms of the human brain into the design of computing algorithms and devices,brain-inspired machine learning has been en-abling computational systems to approach the nature of human-like intelligence.Examples of the successful prac-tice include but are not limited to the hierarchical fea-tures of deep neural networks,low energy cost of spiking neural networks,robustness in recognition,attention mechanism and sparsity for high inference efficiency,mul-timodal information fusion,self-supervised learning,and so forth.With the rapid developments of increased collab-oration between scientists from various disciplines,such as neuroscience,psychology,computer science,engineer-ing,and mathematics,brain-inspired machine learning opens new avenues for exploring cutting-edge methods and technologies in modern AI.
文献关键词：
中图分类号：
作者姓名：
Zhao-Xiang Zhang;Bin Luo;Jin Tang;Shan Yu;Amir Hussain
作者机构：
Institute of Automation,Chinese Academy of Sciences,China;Anhui University,China;Edinburgh Napier University,UK
文献出处：
引用格式：
[1]Zhao-Xiang Zhang;Bin Luo;Jin Tang;Shan Yu;Amir Hussain-.Editorial for Special Issue on Brain-inspired Machine Learning)[J].机器智能研究（英文）,2022(05):347-349
A类：
introdu,timodal
B类：
Editorial,Special,Issue,Brain,inspired,Machine,Learning,recent,years,have,witnessed,significant,progress,artificial,intelligence,Undoubtedly,one,sential,elements,that,contribute,prosperity,cur,rent,brain,machine,learning,By,cing,structural,principles,operational,mechanisms,human,into,design,computing,algorithms,devices,has,been,abling,computational,systems,approach,nature,like,Examples,successful,prac,tice,include,are,not,limited,hierarchical,fea,tures,deep,neural,networks,low,energy,cost,spiking,robustness,recognition,attention,sparsity,high,inference,efficiency,mul,information,fusion,self,supervised,so,forth,With,rapid,developments,increased,collab,oration,between,scientists,from,various,disciplines,such,neuroscience,psychology,computer,engineer,mathematics,opens,new,avenues,exploring,cutting,edge,methods,technologies,modern
AB值：
0.736815
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