典型文献
Towards a New Paradigm for Brain-inspired Computer Vision
文献摘要：
Brain-inspired computer vision aims to learn from biological systems to develop advanced image processing techniques.However,its progress so far is not impressing.We recognize that a main obstacle comes from that the current paradigm for brain-in-spired computer vision has not captured the fundamental nature of biological vision,i.e.,the biological vision is targeted for processing spatio-temporal patterns.Recently,a new paradigm for developing brain-inspired computer vision is emerging,which emphasizes on the spatio-temporal nature of visual signals and the brain-inspired models for processing this type of data.In this paper,we review some re-cent primary works towards this new paradigm,including the development of spike cameras which acquire spiking signals directly from visual scenes,and the development of computational models learned from neural systems that are specialized to process spatio-temporal patterns,including models for object detection,tracking,and recognition.We also discuss about the future directions to improve the paradigm.
文献关键词：
中图分类号：
作者姓名：
Xiao-Long Zou;Tie-Jun Huang;Si Wu
作者机构：
Beijing Academy of Artificial Intelligence,Beijing 100084,China;School of Psychology and Cognitive Sciences,IDG/McGovern Institute for Brain Research,Center for Quantitative Biology,PKU-Tsinghua Center for Life Sciences,Peking University,Beijing 100084,China;National Engineering Research Center of Visual Technology,School of Computer Science,Peking University,Beijing 100871,China;Institute for Artificial Intelligence,Peking University,Beijing 100871,China
文献出处：
引用格式：
[1]Xiao-Long Zou;Tie-Jun Huang;Si Wu-.Towards a New Paradigm for Brain-inspired Computer Vision)[J].机器智能研究（英文）,2022(05):412-424
A类：
impressing
B类：
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AB值：
0.537068
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