中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
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CAS IR Grid
机构
自动化研究所 [12]
采集方式
OAI收割 [12]
内容类型
期刊论文 [11]
会议论文 [1]
发表日期
2023 [1]
2022 [5]
2021 [1]
2020 [1]
2018 [3]
2017 [1]
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A Novel Biologically Inspired Structural Model for Feature Correspondence
期刊论文
OAI收割
IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS, 2023, 卷号: 15, 期号: 2, 页码: 844-854
作者:
Lu, Yan-Feng
;
Yang, Xu
;
Li, Yi
;
Yu, Qian
;
Liu, Zhi-Yong
  |  
收藏
  |  
浏览/下载:19/0
  |  
提交时间:2023/11/17
Visualization
Biological system modeling
Biology
Brain modeling
Biological information theory
Task analysis
Strain
Appearance feature descriptor
biologically inspired model
feature correspondence
feature representation
graph matching (GM)
graph structure
A brain-inspired intention prediction model and its applications to humanoid robot
期刊论文
OAI收割
FRONTIERS IN NEUROSCIENCE, 2022, 卷号: 16, 页码: 11
作者:
Zhao, Yuxuan
;
Zeng, Yi
  |  
收藏
  |  
浏览/下载:38/0
  |  
提交时间:2022/12/27
human-robot interaction
intention prediction
brain-inspired model
spiking neural networks
humanoid robot
Solving the spike feature information vanishing problem in spiking deep Q network with potential based normalization
期刊论文
OAI收割
FRONTIERS IN NEUROSCIENCE, 2022, 卷号: 16, 页码: 11
作者:
Sun, Yinqian
;
Zeng, Yi
;
Li, Yang
  |  
收藏
  |  
浏览/下载:31/0
  |  
提交时间:2022/11/14
brain-inspired decision model
SDQN
reinforcement learning
potential normalization
spiking activity
A Brain-Inspired Theory of Mind Spiking Neural Network for Reducing Safety Risks of Other Agents (vol 16, 753900, 2022)
期刊论文
OAI收割
FRONTIERS IN NEUROSCIENCE, 2022, 卷号: 16, 页码: 2
作者:
Zhao, Zhuoya
;
Lu, Enmeng
;
Zhao, Feifei
;
Zeng, Yi
;
Zhao, Yuxuan
  |  
收藏
  |  
浏览/下载:22/0
  |  
提交时间:2022/07/25
brain-inspired model
safety risks
SNNs
R-STDP
theory of mind
A Brain-Inspired Theory of Mind Spiking Neural Network for Reducing Safety Risks of Other Agents
期刊论文
OAI收割
FRONTIERS IN NEUROSCIENCE, 2022, 卷号: 16, 页码: 13
作者:
Zhao, Zhuoya
;
Lu, Enmeng
;
Zhao, Feifei
;
Zeng, Yi
;
Zhao, Yuxuan
  |  
收藏
  |  
浏览/下载:67/0
  |  
提交时间:2022/07/25
brain-inspired model
safety risks
SNNs
R-STDP
theory of mind
Denoised Internal Models: A Brain-inspired Autoencoder Against Adversarial Attacks
期刊论文
OAI收割
Machine Intelligence Research, 2022, 卷号: 19, 期号: 5, 页码: 456-471
作者:
Kai-Yuan Liu
;
Xing-Yu Li
;
Yu-Rui Lai
;
Hang Su
;
Jia-Chen Wang
  |  
收藏
  |  
浏览/下载:3/0
  |  
提交时间:2024/04/23
Brain-inspired learning
autoencoder
robustness
adversarial attack
generative model
Hierarchical Motion Learning for Goal-Oriented Movements With Speed-Accuracy Tradeoff of a Musculoskeletal System
期刊论文
OAI收割
IEEE TRANSACTIONS ON CYBERNETICS, 2021, 页码: 14
作者:
Zhou, Junjie
;
Zhong, Shanlin
;
Wu, Wei
  |  
收藏
  |  
浏览/下载:28/0
  |  
提交时间:2022/01/27
Muscles
Adaptation models
Task analysis
Arms
Mathematical model
Integrated circuit modeling
Basal ganglia
Brain-inspired decision making
Fitts' law
motion generation
musculoskeletal system
speed-accuracy tradeoff (SAT)
A Brain-Inspired Model of Theory of Mind
期刊论文
OAI收割
FRONTIERS IN NEUROROBOTICS, 2020, 卷号: 14, 页码: 17
作者:
Zeng, Yi
;
Zhao, Yuxuan
;
Zhang, Tielin
;
Zhao, Dongcheng
;
Zhao, Feifei
  |  
收藏
  |  
浏览/下载:49/0
  |  
提交时间:2021/01/07
theory of mind
false-belief task
brain inspired model
self-experience
connection maturation
inhibitory control
Brain-Inspired Motion Learning in Recurrent Neural Network With Emotion Modulation
期刊论文
OAI收割
IEEE Transactions on Cognitive and Developmental Systems, 2018, 卷号: 10, 期号: 4, 页码: 1153 - 1164
作者:
Xiao Huang
;
Wei Wu
;
Hong Qiao
;
Yidao Ji
;
Qiao, Hong
  |  
收藏
  |  
浏览/下载:13/0
  |  
提交时间:2020/06/09
Brain-inspired model
emotion
motion learning
recurrent neural network
A Basal Ganglia Network Centric Reinforcement Learning Model and Its Application in Unmanned Aerial Vehicle
期刊论文
OAI收割
IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS, 2018, 卷号: 10, 期号: 2, 页码: 290-303
作者:
Zeng, Yi
;
Wang, Guixiang
;
Xu, Bo
  |  
收藏
  |  
浏览/下载:31/0
  |  
提交时间:2019/12/16
Basal ganglia (BG) network
brain-inspired intelligence
precise encoding
reinforcement learning model
unmanned aerial vehicle (UAV) autonomous learning