CASIA OpenIR
(本次检索基于用户作品认领结果)

浏览/检索结果: 共5条,第1-5条 帮助

限定条件            
已选(0)清除 条数/页:   排序方式:
Decoding Visual Neural Representations by Multimodal Learning of Brain-Visual-Linguistic Features 期刊论文
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023, 页码: 1-17
作者:  Du CD(杜长德);  Fu KC(付铠成);  Li JP(李劲鹏);  He HG(何晖光)
Adobe PDF(4669Kb)  |  收藏  |  浏览/下载:378/65  |  提交时间:2023/05/05
Multi-View Multi-Label Fine-Grained Emotion Decoding From Human Brain Activity 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 页码: 15
作者:  Fu, Kaicheng;  Du, Changde;  Wang, Shengpei;  He, Huiguang
Adobe PDF(4570Kb)  |  收藏  |  浏览/下载:245/61  |  提交时间:2022/12/27
Decoding  Brain modeling  Functional magnetic resonance imaging  Predictive models  Emotion recognition  Dimensionality reduction  Pattern recognition  Fine-grained emotion decoding  multi-label learning  multi-view learning  product of experts (PoEs)  variational autoencoder  
Exploring the brain-like properties of deep neural networks: a neural encoding perspective 期刊论文
Machine Intelligence Research, 2022, 卷号: 19, 期号: 5, 页码: 439-455
作者:  Qiongyi Zhou;  Changde Du;  Huiguang He
Adobe PDF(6004Kb)  |  收藏  |  浏览/下载:169/36  |  提交时间:2023/01/17
Multi-Modal Domain Adaptation Variational Autoencoder for EEG-Based Emotion Recognition 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2022, 卷号: 9, 期号: 9, 页码: 1612-1626
作者:  Yixin Wang;  Shuang Qiu;  Dan Li;  Changde Du;  Bao-Liang Lu;  Huiguang He
Adobe PDF(1908Kb)  |  收藏  |  浏览/下载:251/56  |  提交时间:2022/08/19
Cycle-consistency  domain adaptation  electroencephalograph (EEG)  multi modality  variational autoencoder  
Exploring the Brain-like Properties of Deep Neural Networks: A Neural Encoding Perspective 期刊论文
Machine Intelligence Research, 2022, 卷号: 19, 期号: 5, 页码: 439-455
作者:  Qiongyi Zhou;  Changde Du;  Huiguang He
Adobe PDF(7698Kb)  |  收藏  |  浏览/下载:3/0  |  提交时间:2024/04/23
Convolutional neural network (CNN)  vision transformer (ViT)  multi-modal networks  spatial-temporal networks  visual neural encoding  brain-like neural networks