中文版 | English

在结果中检索

CASIA OpenIR

浏览/检索结果: 共10条，第1-10条 帮助

限定条件                    
已选(0)清除 条数/页：   排序方式：
Dynamic fusion of convolutional features based on spatial and temporal attention for visual tracking 会议论文
, Budapest, Hungary, 14-19 July 2019
作者:  Zhao, Dongcheng;  Zeng, Yi
Adobe PDF(1953Kb)  |  收藏  |  浏览/下载：191/55  |  提交时间：2021/06/10
Paraventricular Thalamus  Spatial Attention  Temporal Attention  
Multimodal data revealed different neurobiological correlates of intelligence between males and females 期刊论文
BRAIN IMAGING AND BEHAVIOR, 2019, 卷号: 14, 期号: NA, 页码: 1-15
作者:  Jiang, Rongtao;  Calhoun, Vince D.;  Cui, Yue;  Qi, Shile;  Zhuo, Chuanjun;  Li, Jin;  Jung, Rex;  Yang, Jian;  Du, Yuhui;  Jiang, Tianzi;  Sui, Jing
浏览  |  Adobe PDF(3381Kb)  |  收藏  |  浏览/下载：273/83  |  提交时间：2020/06/13
Connectome-based predictive modeling  Gender difference  Individualized prediction  Intelligence quotient  Multimodal  
Reconstructing Perceived Images From Human Brain Activities With Bayesian Deep Multiview Learning 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2019, 卷号: 30, 期号: 8, 页码: 2310-2323
作者:  Du, Changde;  Du, Changying;  Huang, Lijie;  He, Huiguang
Adobe PDF(3773Kb)  |  收藏  |  浏览/下载：356/44  |  提交时间：2019/12/16
Deep neural network (DNN)  image reconstruction  multiview learning  neural decoding  variational Bayesian inference  
Discriminating schizophrenia using recurrent neural network applied on time courses of multi-site FMRI data 期刊论文
EBIOMEDICINE, 2019, 卷号: 47, 页码: 543-552
作者:  Yan, Weizheng;  Calhoun, Vince;  Song, Ming;  Cui, Yue;  Yan, Hao;  Liu, Shengfeng;  Fan, Lingzhong;  Zuo, Nianming;  Yang, Zhengyi;  Xu, Kaibin;  Yan, Jun;  Lv, Luxian;  Chen, Jun;  Chen, Yunchun;  Guo, Hua;  Li, Peng;  Lu, Lin;  Wan, Ping;  Wang, Huaning;  Wang, Huiling;  Yang, Yongfeng;  Zhang, Hongxing;  Zhang, Dai;  Jiang, Tianzi;  Sui, Jing
Adobe PDF(2166Kb)  |  收藏  |  浏览/下载：418/67  |  提交时间：2019/12/16
Recurrent neural network (RNN)  Schizophrenia  Multi-site classification  fMRI  Striatum  Cerebellum  Deep learning  
Pairwise Interactions among Brain Regions Organize Large-Scale Functional Connectivity during Execution of Various Tasks 期刊论文
NEUROSCIENCE, 2019, 卷号: 412, 页码: 190-206
作者:  Niu, Weikun;  Huang, Xuhui;  Xu, Kaibin;  Jiang, Tianzi;  Yu, Shan
Adobe PDF(7177Kb)  |  收藏  |  浏览/下载：400/68  |  提交时间：2019/12/16
task state fMRI  pairwise correlation  functional network  neural network model  
Activation-based association profiles differentiate network roles across cognitive loads 期刊论文
HUMAN BRAIN MAPPING, 2019, 卷号: 40, 期号: 9, 页码: 2800-2812
作者:  Zuo, Nianming;  Salami, Alireza;  Yang, Yihong;  Yang, Zhengyi;  Sui, Jing;  Jian, Tianzi
浏览  |  Adobe PDF(2320Kb)  |  收藏  |  浏览/下载：478/108  |  提交时间：2019/07/12
association  cognitive performance  functional activation  functional magnetic resonance imaging (fMRI)  working memory  
Schizophrenia-related abnormalities in the triple network: A meta-analysis of working memory studies 期刊论文
Brain Imaging and Behavior, 2019, 卷号: 14, 期号: 暂无, 页码: 暂无
作者:  Wu DY(吴东亚)
浏览  |  Adobe PDF(538Kb)  |  收藏  |  浏览/下载：205/0  |  提交时间：2019/06/19
Schizophrenia, Meta-analysis, Neuroimaging, Working Memory  
MIR137 polygenic risk is associated with schizophrenia and affects functional connectivity of the dorsolateral prefrontal cortex 期刊论文
Psychological Medicine, 2019, 期号: 无, 页码: 无
作者:  Liu Shu;  Li Ang;  Liu Yong;  Li Jin;  Wang Meng;  Sun Yuqing;  Qin Wen;  Yu Chunshui;  Jiang Tianzi;  Liu Bing
浏览  |  Adobe PDF(850Kb)  |  收藏  |  浏览/下载：373/125  |  提交时间：2019/06/18
Dorsolateral Prefrontal Cortex  Functional Connectivity  Microrna-137  Polygenic Risk Score  Schizophrenia  
人工神经网络中连续学习与情境学习的算法设计与研究 研究报告
2019
作者:  陈阳
浏览  |  Adobe PDF(2342Kb)  |  收藏  |  浏览/下载：377/122  |  提交时间：2019/05/09
类脑智能，连续学习，情境学习，正交权重修改算法，情境信息处理模块  
Brain Encoding and Decoding in fMRI with Bidirectional Deep Generative Models 期刊论文
Engineering, 2019, 期号: 0, 页码: 1-8
作者:  Du Changde;  Li Jinpeng;  Huang Lijie;  He Huiguang
浏览  |  Adobe PDF(497Kb)  |  收藏  |  浏览/下载：534/179  |  提交时间：2019/05/06
Brain Encoding And Decoding  Fmri  Deep Neural Networks  Deep Generative Models  Dual Learning