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吕宝粮
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- affiliation: Shanghai Jiao Tong University, Shanghai, China
- unicode name: 吕宝粮
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2020 – today
- 2024
[c211]Ziyi Li, Li-Ming Zhao, Wei-Long Zheng, Bao-Liang Lu:
Temporal-Spatial Prediction: Pre-Training on Diverse Datasets for EEG Classification. ICASSP 2024: 1806-1810- [c210]Wei-Bang Jiang, Ziyi Li, Wei-Long Zheng, Bao-Liang Lu:
Functional Emotion Transformer for EEG-Assisted Cross-Modal Emotion Recognition. ICASSP 2024: 1841-1845 - [c209]Yu-Ting Lan, Wei-Bang Jiang, Wei-Long Zheng, Bao-Liang Lu:
CEMOAE: A Dynamic Autoencoder with Masked Channel Modeling for Robust EEG-Based Emotion Recognition. ICASSP 2024: 1871-1875 - [c208]Pengxuan Gao, Tianyu Liu, Jia-Wen Liu, Bao-Liang Lu, Wei-Long Zheng:
Multimodal Multi-View Spectral-Spatial-Temporal Masked Autoencoder for Self-Supervised Emotion Recognition. ICASSP 2024: 1926-1930 - [c207]Wei-Bang Jiang, Li-Ming Zhao, Bao-Liang Lu:
Large Brain Model for Learning Generic Representations with Tremendous EEG Data in BCI. ICLR 2024 - [c206]Tian-Fang Ma, Lu-Yu Liu, Li-Ming Zhao, Dan Peng, Yong Lu, Wei-Long Zheng, Bao-Liang Lu:
Detecting Major Depression Disorder with Multiview Eye Movement Features in a Novel Oil Painting Paradigm. IJCNN 2024: 1-8 - [i21]Wei-Bang Jiang, Li-Ming Zhao, Bao-Liang Lu:
Large Brain Model for Learning Generic Representations with Tremendous EEG Data in BCI. CoRR abs/2405.18765 (2024) - [i20]Tian-Hua Li, Tian-Fang Ma, Dan Peng, Wei-Long Zheng, Bao-Liang Lu:
Focused State Recognition Using EEG with Eye Movement-Assisted Annotation. CoRR abs/2407.09508 (2024) - [i19]Yifei Yang, Runhan Shi, Zuchao Li, Shu Jiang, Bao-Liang Lu, Yang Yang, Hai Zhao:
BatGPT-Chem: A Foundation Large Model For Retrosynthesis Prediction. CoRR abs/2408.10285 (2024) - 2023
- [j70]Dongrui Wu
, Bao-Liang Lu, Bin Hu, Zhigang Zeng:
Affective Brain-Computer Interfaces (aBCIs): A Tutorial. Proc. IEEE 111(10): 1314-1332 (2023) - [j69]Yong Peng, Keding Chen, Feiping Nie, Bao-Liang Lu, Wanzeng Kong:
Two-Dimensional Embedded Fuzzy Data Clustering. IEEE Trans. Emerg. Top. Comput. Intell. 7(4): 1263-1275 (2023) - [j68]Yong Peng, Wenna Huang, Wanzeng Kong, Feiping Nie, Bao-Liang Lu:
JGSED: An End-to-End Spectral Clustering Model for Joint Graph Construction, Spectral Embedding and Discretization. IEEE Trans. Emerg. Top. Comput. Intell. 7(6): 1687-1701 (2023) - [j67]Yong Peng, Honggang Liu, Wanzeng Kong, Feiping Nie, Bao-Liang Lu, Andrzej Cichocki:
Joint EEG Feature Transfer and Semisupervised Cross-Subject Emotion Recognition. IEEE Trans. Ind. Informatics 19(7): 8104-8115 (2023) - [c205]Jing-Yi Liu, Jia-Wen Liu, Wei-Long Zheng, Bao-Liang Lu:
Transformer-Based Domain Adaptation for Multi-Modal Emotion Recognition in Response to Game Animation Videos. BIBM 2023: 879-884 - [c204]Rong-Fei Gu, Li-Ming Zhao, Wei-Long Zheng, Bao-Liang Lu:
Tagging Continuous Labels for EEG-based Emotion Classification. EMBC 2023: 1-4 - [c203]Yu-Ting Lan, Dan Peng, Wei Liu, Yun Luo, Ziyu Mao, Wei-Long Zheng, Bao-Liang Lu:
Investigating Emotion EEG Patterns for Depression Detection with Attentive Simple Graph Convolutional Network. EMBC 2023: 1-4 - [c202]Luyu Liu, Dan Peng, Wei-Long Zheng, Bao-Liang Lu:
Objective Depression Detection Using EEG and Eye Movement Signals Induced by Oil Paintings. EMBC 2023: 1-4 - [c201]Dan Peng, Wei Liu, Yun Luo, Ziyu Mao, Wei-Long Zheng, Bao-Liang Lu:
Deep Depression Detection with Resting-State and Cognitive-Task EEG. EMBC 2023: 1-4 - [c200]Wei-Bang Jiang, Xu Yan, Wei-Long Zheng, Bao-Liang Lu:
Elastic Graph Transformer Networks for EEG-Based Emotion Recognition. ICASSP 2023: 1-5 - [c199]Xuan-Hao Liu, Wei-Bang Jiang, Wei-Long Zheng, Bao-Liang Lu:
Two-Stream Spectral-Temporal Denoising Network for End-to-End Robust EEG-Based Emotion Recognition. ICONIP (3) 2023: 186-197 - [c198]Jian-Ming Zhang, Jiawen Liu, Ziyi Li, Tian-Fang Ma, Yiting Wang, Wei-Long Zheng, Bao-Liang Lu:
Naturalistic Emotion Recognition Using EEG and Eye Movements. ICONIP (3) 2023: 265-276 - [c197]Zhong-Wei Jin, Jiawen Liu, Wei-Long Zheng, Bao-Liang Lu:
DAformer: Transformer with Domain Adversarial Adaptation for EEG-Based Emotion Recognition with Live-Oil Paintings. ICONIP (9) 2023: 402-414 - [c196]Rong-Fei Gu, Rui Li, Wei-Long Zheng, Bao-Liang Lu:
Cross-Subject Decision Confidence Estimation from EEG Signals Using Spectral-Spatial-Temporal Adaptive GCN with Domain Adaptation. IJCNN 2023: 1-8 - [c195]Wei-Bang Jiang, Xuan-Hao Liu, Wei-Long Zheng, Bao-Liang Lu:
Multimodal Adaptive Emotion Transformer with Flexible Modality Inputs on A Novel Dataset with Continuous Labels. ACM Multimedia 2023: 5975-5984 - [c194]Cheng Fei, Rui Li, Li-Ming Zhao, Wei-Long Zheng, Bao-Liang Lu:
EEG-Eye Movements Cross-Modal Decision Confidence Measurement with Generative Adversarial Networks. NER 2023: 1-4 - [c193]Yu-Ting Lan, Ze-Chen Li, Dan Peng, Wei-Long Zheng, Bao-Liang Lu:
Identifying Artistic Expertise Difference in Emotion Recognition in Response to Oil Paintings. NER 2023: 1-4 - [i18]Yu-Ting Lan, Kan Ren, Yansen Wang, Wei-Long Zheng, Dongsheng Li, Bao-Liang Lu, Lili Qiu:
Seeing through the Brain: Image Reconstruction of Visual Perception from Human Brain Signals. CoRR abs/2308.02510 (2023) - 2022
- [j66]Yixin Wang, Shuang Qiu, Dan Li, Changde Du, Bao-Liang Lu, Huiguang He:
Multi-Modal Domain Adaptation Variational Autoencoder for EEG-Based Emotion Recognition. IEEE CAA J. Autom. Sinica 9(9): 1612-1626 (2022) - [j65]Fangyao Shen, Yong Peng, Guojun Dai, Bao-Liang Lu, Wanzeng Kong:
Coupled Projection Transfer Metric Learning for Cross-Session Emotion Recognition from EEG. Syst. 10(2): 47 (2022) - [j64]Yong Peng, Wenjuan Wang, Wanzeng Kong, Feiping Nie, Bao-Liang Lu, Andrzej Cichocki:
Joint Feature Adaptation and Graph Adaptive Label Propagation for Cross-Subject Emotion Recognition From EEG Signals. IEEE Trans. Affect. Comput. 13(4): 1941-1958 (2022) - [j63]Shu Jiang, Zuchao Li, Hai Zhao, Bao-Liang Lu, Rui Wang:
Tri-training for Dependency Parsing Domain Adaptation. ACM Trans. Asian Low Resour. Lang. Inf. Process. 21(3): 48:1-48:17 (2022) - [j62]Dongrui Wu, Yifan Xu, Bao-Liang Lu:
Transfer Learning for EEG-Based Brain-Computer Interfaces: A Review of Progress Made Since 2016. IEEE Trans. Cogn. Dev. Syst. 14(1): 4-19 (2022) - [j61]Wei Liu, Jie-Lin Qiu, Wei-Long Zheng, Bao-Liang Lu:
Comparing Recognition Performance and Robustness of Multimodal Deep Learning Models for Multimodal Emotion Recognition. IEEE Trans. Cogn. Dev. Syst. 14(2): 715-729 (2022) - [j60]Xing Li, Fangyao Shen, Yong Peng, Wanzeng Kong, Bao-Liang Lu:
Efficient Sample and Feature Importance Mining in Semi-Supervised EEG Emotion Recognition. IEEE Trans. Circuits Syst. II Express Briefs 69(7): 3349-3353 (2022) - [j59]Wei Wu, Wei Sun, Q. M. Jonathan Wu, Yimin Yang, Hui Zhang, Wei-Long Zheng, Bao-Liang Lu:
Multimodal Vigilance Estimation Using Deep Learning. IEEE Trans. Cybern. 52(5): 3097-3110 (2022) - [j58]Yong Peng, Yikai Zhang, Wanzeng Kong, Feiping Nie, Bao-Liang Lu, Andrzej Cichocki:
S3LRR: A Unified Model for Joint Discriminative Subspace Identification and Semisupervised EEG Emotion Recognition. IEEE Trans. Instrum. Meas. 71: 1-13 (2022) - [j57]Yikai Zhang, Ruiqi Guo, Yong Peng, Wanzeng Kong, Feiping Nie, Bao-Liang Lu:
An Auto-Weighting Incremental Random Vector Functional Link Network for EEG-Based Driving Fatigue Detection. IEEE Trans. Instrum. Meas. 71: 1-14 (2022) - [c192]Cheng Fei, Rui Li, Li-Ming Zhao, Ziyi Li, Bao-Liang Lu:
A Cross-modality Deep Learning Method for Measuring Decision Confidence from Eye Movement Signals. EMBC 2022: 3342-3345 - [c191]Shuai Luo, Yu-Ting Lan, Dan Peng, Ziyi Li, Wei-Long Zheng, Bao-Liang Lu:
Multimodal Emotion Recognition in Response to Oil Paintings. EMBC 2022: 4167-4170 - [c190]Ziyi Li, Luyu Liu, Yihui Zhu, Bao-Liang Lu:
Exploring Sex Differences in Key Frequency Bands and Channel Connections for EEG-based Emotion Recognition. EMBC 2022: 4793-4796 - [c189]Rui Li, Yiting Wang, Bao-Liang Lu:
Measuring Decision Confidence Levels from EEG Using a Spectral-Spatial-Temporal Adaptive Graph Convolutional Neural Network. ICONIP (5) 2022: 395-406 - [c188]Tian-Fang Ma, Wei-Long Zheng, Bao-Liang Lu:
Few-Shot Class-Incremental Learning for EEG-Based Emotion Recognition. ICONIP (5) 2022: 445-455 - [c187]Yan-Kai Liu, Wei-Bang Jiang, Bao-Liang Lu:
Increasing the Stability of EEG-based Emotion Recognition with a Variant of Neural Processes. IJCNN 2022: 1-6 - [c186]Rui Li, Yiting Wang, Wei-Long Zheng, Bao-Liang Lu:
A Multi-view Spectral-Spatial-Temporal Masked Autoencoder for Decoding Emotions with Self-supervised Learning. ACM Multimedia 2022: 6-14 - 2021
- [j56]Shu Jiang, Zhuosheng Zhang, Hai Zhao, Jiangtong Li, Yang Yang, Bao-Liang Lu, Ning Xia:
When SMILES Smiles, Practicality Judgment and Yield Prediction of Chemical Reaction via Deep Chemical Language Processing. IEEE Access 9: 85071-85083 (2021) - [j55]Shu Jiang, Rui Wang, Zuchao Li, Masao Utiyama, Kehai Chen, Eiichiro Sumita, Hai Zhao, Bao-Liang Lu:
Document-Level Neural Machine Translation with Associated Memory Network. IEICE Trans. Inf. Syst. 104-D(10): 1712-1723 (2021) - [j54]Wei Wu, Q. M. Jonathan Wu, Wei Sun, Yimin Yang, Xiaofang Yuan, Wei-Long Zheng, Bao-Liang Lu:
A Regression Method With Subnetwork Neurons for Vigilance Estimation Using EOG and EEG. IEEE Trans. Cogn. Dev. Syst. 13(1): 209-222 (2021) - [j53]Wei Wu, Wei Sun, Q. M. Jonathan Wu, Cheng Zhang, Yimin Yang, Hongshan Yu, Bao-Liang Lu:
Faster Single Model Vigilance Detection Based on Deep Learning. IEEE Trans. Cogn. Dev. Syst. 13(3): 621-630 (2021) - [j52]Yong Peng, Wanzeng Kong, Feiwei Qin, Feiping Nie, Jinglong Fang, Bao-Liang Lu, Andrzej Cichocki:
Self-Weighted Semi-Supervised Classification for Joint EEG-Based Emotion Recognition and Affective Activation Patterns Mining. IEEE Trans. Instrum. Meas. 70: 1-11 (2021) - [c185]Li-Ming Zhao, Xu Yan, Bao-Liang Lu:
Plug-and-Play Domain Adaptation for Cross-Subject EEG-based Emotion Recognition. AAAI 2021: 863-870 - [c184]Wei-Bang Jiang, Li-Ming Zhao, Ping Guo, Bao-Liang Lu:
Discriminating Surprise and Anger from EEG and Eye Movements with a Graph Network. BIBM 2021: 1353-1357 - [c183]Yun Luo, Bao-Liang Lu:
Wasserstein-Distance-Based Multi-Source Adversarial Domain Adaptation for Emotion Recognition and Vigilance Estimation. BIBM 2021: 1424-1428 - [c182]Yiting Wang, Wei-Bang Jiang, Rui Li, Bao-Liang Lu:
Emotion Transformer Fusion: Complementary Representation Properties of EEG and Eye Movements on Recognizing Anger and Surprise. BIBM 2021: 1575-1578 - [c181]Hao-Yi Hu, Li-Ming Zhao, Yu-Zhong Liu, Hua-Liang Li, Bao-Liang Lu:
A Novel Experiment Setting for Cross-subject Emotion Recognition. EMBC 2021: 6416-6419 - [c180]Rui-Xiao Ma, Xu Yan, Yu-Zhong Liu, Hua-Liang Li, Bao-Liang Lu:
Sex Difference in Emotion Recognition under Sleep Deprivation: Evidence from EEG and Eye-tracking. EMBC 2021: 6449-6452 - [c179]Jian-Ming Zhang, Xu Yan, Zi-Yi Li, Li-Ming Zhao, Yu-Zhong Liu, Hua-Liang Li, Bao-Liang Lu:
A Cross-subject and Cross-modal Model for Multimodal Emotion Recognition. ICONIP (6) 2021: 203-211 - [c178]Le-Dian Liu, Rui Li, Yu-Zhong Liu, Hua-Liang Li, Bao-Liang Lu:
EEG-Based Human Decision Confidence Measurement Using Graph Neural Networks. ICONIP (6) 2021: 291-298 - [c177]Xu Yan, Li-Ming Zhao, Bao-Liang Lu:
Simplifying Multimodal Emotion Recognition with Single Eye Movement Modality. ACM Multimedia 2021: 1057-1063 - [c176]Rui Li, Yiting Wang, Bao-Liang Lu:
A Multi-Domain Adaptive Graph Convolutional Network for EEG-based Emotion Recognition. ACM Multimedia 2021: 5565-5573 - [c175]Zhi-Wei Zhao, Wei Liu, Bao-Liang Lu:
Multimodal Emotion Recognition Using a Modified Dense Co-Attention Symmetric Network. NER 2021: 73-76 - [c174]Rui Li, Le-Dian Liu, Bao-Liang Lu:
Measuring Human Decision Confidence from EEG Signals in an Object Detection Task. NER 2021: 942-945 - [c173]Rui Li, Le-Dian Liu, Bao-Liang Lu:
Discrimination of Decision Confidence Levels from EEG Signals. NER 2021: 946-949 - 2020
- [j51]Yingying Jiao, Yini Deng, Yun Luo, Bao-Liang Lu:
Driver sleepiness detection from EEG and EOG signals using GAN and LSTM networks. Neurocomputing 408: 100-111 (2020) - [j50]Wei-Long Zheng, Kunpeng Gao, Gang Li, Wei Liu, Chao Liu, Jing-Quan Liu, Guoxing Wang, Bao-Liang Lu:
Vigilance Estimation Using a Wearable EOG Device in Real Driving Environment. IEEE Trans. Intell. Transp. Syst. 21(1): 170-184 (2020) - [c172]Chen-Li Yao, Bao-Liang Lu:
A Robust Approach to Estimating Vigilance from EEG with Neural Processes. BIBM 2020: 1202-1205 - [c171]Wenrui Mu, Bao-Liang Lu:
Examining Four Experimental Paradigms for EEG-Based Sleep Quality Evaluation with Domain Adaptation. EMBC 2020: 5913-5916 - [c170]Yong Peng, Qingxi Li, Wanzeng Kong, Jianhai Zhang, Bao-Liang Lu, Andrzej Cichocki:
Joint Semi-Supervised Feature Auto-Weighting and Classification Model for EEG-Based Cross-Subject Sleep Quality Evaluation. ICASSP 2020: 946-950 - [c169]Yu-Ting Lan, Wei Liu, Bao-Liang Lu:
Multimodal Emotion Recognition Using Deep Generalized Canonical Correlation Analysis with an Attention Mechanism. IJCNN 2020: 1-6 - [c168]Le-Yan Tao, Bao-Liang Lu:
Emotion Recognition under Sleep Deprivation Using a Multimodal Residual LSTM Network. IJCNN 2020: 1-8 - [c167]Hao Tang, Zhiao Huang, Jiayuan Gu, Bao-Liang Lu, Hao Su:
Towards Scale-Invariant Graph-related Problem Solving by Iterative Homogeneous GNNs. NeurIPS 2020 - [i17]Xun Wu, Wei-Long Zheng, Bao-Liang Lu:
Investigating EEG-Based Functional Connectivity Patterns for Multimodal Emotion Recognition. CoRR abs/2004.01973 (2020) - [i16]Dongrui Wu, Yifan Xu, Bao-Liang Lu:
Transfer Learning for EEG-Based Brain-Computer Interfaces: A Review of Progresses Since 2016. CoRR abs/2004.06286 (2020) - [i15]Yun Luo, Li-Zhen Zhu, Zi-Yu Wan, Bao-Liang Lu:
Data Augmentation for Enhancing EEG-based Emotion Recognition with Deep Generative Models. CoRR abs/2006.05331 (2020) - [i14]Shu Jiang, Hai Zhao, Zuchao Li, Bao-Liang Lu:
Document-level Neural Machine Translation with Document Embeddings. CoRR abs/2009.08775 (2020) - [i13]Hao Tang, Zhiao Huang, Jiayuan Gu, Bao-Liang Lu, Hao Su:
Towards Scale-Invariant Graph-related Problem Solving by Iterative Homogeneous Graph Neural Networks. CoRR abs/2010.13547 (2020)
2010 – 2019
- 2019
- [j49]Huangfei Jiang, Xiya Guan, Wei-Ye Zhao, Li-Ming Zhao, Bao-Liang Lu:
Generating Multimodal Features for Emotion Classification from Eye Movement Signals. Aust. J. Intell. Inf. Process. Syst. 15(3): 59-66 (2019) - [j48]Wei-Long Zheng, Jia-Yi Zhu, Bao-Liang Lu:
Identifying Stable Patterns over Time for Emotion Recognition from EEG. IEEE Trans. Affect. Comput. 10(3): 417-429 (2019) - [j47]Wei-Long Zheng, Wei Liu, Yifei Lu, Bao-Liang Lu, Andrzej Cichocki:
EmotionMeter: A Multimodal Framework for Recognizing Human Emotions. IEEE Trans. Cybern. 49(3): 1110-1122 (2019) - [c166]Jiang-Jian Guo, Rong Zhou, Li-Ming Zhao, Bao-Liang Lu:
Multimodal Emotion Recognition from Eye Image, Eye Movement and EEG Using Deep Neural Networks. EMBC 2019: 3071-3074 - [c165]Lan-Qing Bao, Jie-Lin Qiu, Hao Tang, Wei-Long Zheng, Bao-Liang Lu:
Investigating Sex Differences in Classification of Five Emotions from EEG and Eye Movement Signals. EMBC 2019: 6746-6749 - [c164]Bo-Qun Ma, He Li, Wei-Long Zheng, Bao-Liang Lu:
Reducing the Subject Variability of EEG Signals with Adversarial Domain Generalization. ICONIP (1) 2019: 30-42 - [c163]Lu Gan, Wei Liu, Yun Luo, Xun Wu, Bao-Liang Lu:
A Cross-Culture Study on Multimodal Emotion Recognition Using Deep Learning. ICONIP (4) 2019: 670-680 - [c162]Bo-Qun Ma, He Li, Yun Luo, Bao-Liang Lu:
Depersonalized Cross-Subject Vigilance Estimation with Adversarial Domain Generalization. IJCNN 2019: 1-8 - [c161]Yun Luo, Li-Zhen Zhu, Bao-Liang Lu:
A GAN-Based Data Augmentation Method for Multimodal Emotion Recognition. ISNN (1) 2019: 141-150 - [c160]Jia-Xin Ma, Hao Tang, Wei-Long Zheng, Bao-Liang Lu:
Emotion Recognition using Multimodal Residual LSTM Network. ACM Multimedia 2019: 176-183 - [c159]Xun Wu, Wei-Long Zheng, Bao-Liang Lu:
Identifying Functional Brain Connectivity Patterns for EEG-Based Emotion Recognition. NER 2019: 235-238 - [c158]Tian-Hao Li, Wei Liu, Wei-Long Zheng, Bao-Liang Lu:
Classification of Five Emotions from EEG and Eye Movement Signals: Discrimination Ability and Stability over Time. NER 2019: 607-610 - [c157]Li-Ming Zhao, Rui Li, Wei-Long Zheng, Bao-Liang Lu:
Classification of Five Emotions from EEG and Eye Movement Signals: Complementary Representation Properties. NER 2019: 611-614 - [i12]Shu Jiang, Zhuosheng Zhang, Hai Zhao, Jiangtong Li, Yang Yang, Bao-Liang Lu, Ning Xia:
Judging Chemical Reaction Practicality From Positive Sample only Learning. CoRR abs/1904.09824 (2019) - [i11]Wei Liu, Jie-Lin Qiu, Wei-Long Zheng, Bao-Liang Lu:
Multimodal Emotion Recognition Using Deep Canonical Correlation Analysis. CoRR abs/1908.05349 (2019) - [i10]Shu Jiang, Rui Wang, Zuchao Li, Masao Utiyama, Kehai Chen, Eiichiro Sumita, Hai Zhao, Bao-Liang Lu:
Document-level Neural Machine Translation with Inter-Sentence Attention. CoRR abs/1910.14528 (2019) - 2018
- [j46]Rui Wang, Hai Zhao, Sabine Ploux, Bao-Liang Lu, Masao Utiyama, Eiichiro Sumita:
Graph-Based Bilingual Word Embedding for Statistical Machine Translation. ACM Trans. Asian Low Resour. Lang. Inf. Process. 17(4): 31:1-31:23 (2018) - [j45]Yimin Yang, Q. M. Jonathan Wu, Wei-Long Zheng, Bao-Liang Lu:
EEG-Based Emotion Recognition Using Hierarchical Network With Subnetwork Nodes. IEEE Trans. Cogn. Dev. Syst. 10(2): 408-419 (2018) - [c156]Jie-Lin Qiu, Wei Liu, Bao-Liang Lu:
Multi-view Emotion Recognition Using Deep Canonical Correlation Analysis. ICONIP (5) 2018: 221-231 - [c155]Yun Luo, Si-Yang Zhang, Wei-Long Zheng, Bao-Liang Lu:
WGAN Domain Adaptation for EEG-Based Emotion Recognition. ICONIP (5) 2018: 275-286 - [c154]Li-Ming Zhao, Xin-Wei Li, Wei-Long Zheng, Bao-Liang Lu:
Active Feedback Framework with Scan-Path Clustering for Deep Affective Models. ICONIP (2) 2018: 330-340 - [c153]He Li, Yi-Ming Jin, Wei-Long Zheng, Bao-Liang Lu:
Cross-Subject Emotion Recognition Using Deep Adaptation Networks. ICONIP (5) 2018: 403-413 - [c152]Yini Deng, Yingying Jiao, Bao-Liang Lu:
Driver Sleepiness Detection Using LSTM Neural Network. ICONIP (4) 2018: 622-633 - [c151]He Li, Wei-Long Zheng, Bao-Liang Lu:
Multimodal Vigilance Estimation with Adversarial Domain Adaptation Networks. IJCNN 2018: 1-6 - [c150]Jia-Jun Tong, Yun Luo, Bo-Qun Ma, Wei-Long Zheng, Bao-Liang Lu, Xiao-Qi Song, Shi-Wei Ma:
Sleep Quality Estimation with Adversarial Domain Adaptation: From Laboratory to Real Scenario. IJCNN 2018: 1-8 - [c149]Changde Du, Changying Du, Hao Wang, Jinpeng Li, Wei-Long Zheng, Bao-Liang Lu, Huiguang He:
Semi-supervised Deep Generative Modelling of Incomplete Multi-Modality Emotional Data. ACM Multimedia 2018: 108-116 - [i9]Changde Du, Changying Du, Hao Wang, Jinpeng Li, Wei-Long Zheng, Bao-Liang Lu, Huiguang He:
Semi-supervised Deep Generative Modelling of Incomplete Multi-Modality Emotional Data. CoRR abs/1808.02096 (2018) - 2017
- [j44]Yong Peng, Bao-Liang Lu:
Discriminative extreme learning machine with supervised sparsity preserving for image classification. Neurocomputing 261: 242-252 (2017) - [j43]Kai-Ming Jiang, Ya-Jing Chen, Jin-Xiong Lv, Bao-Liang Lu, Lei Xu:
Bootstrapping integrative hypothesis test for identifying biomarkers that differentiates lung cancer and chronic obstructive pulmonary disease. Neurocomputing 269: 40-46 (2017) - [j42]Yong Peng, Bao-Liang Lu:
Robust structured sparse representation via half-quadratic optimization for face recognition. Multim. Tools Appl. 76(6): 8859-8880 (2017) - [j41]Wei-Long Zheng, Shan-Chun Shen, Bao-Liang Lu:
Online Depth Image-Based Object Tracking with Sparse Representation and Object Detection. Neural Process. Lett. 45(3): 745-758 (2017) - [c148]Yingying Jiao, Bao-Liang Lu:
Detecting driver sleepiness from EEG alpha wave during daytime driving. BIBM 2017: 728-731 - [c147]Xue Yan, Wei-Long Zheng, Wei Liu, Bao-Liang Lu:
Identifying Gender Differences in Multimodal Emotion Recognition Using Bimodal Deep AutoEncoder. ICONIP (4) 2017: 533-542 - [c146]Xing-Zan Zhang, Wei-Long Zheng, Bao-Liang Lu:
EEG-Based Sleep Quality Evaluation with Deep Transfer Learning. ICONIP (4) 2017: 543-552 - [c145]Wei-Ye Zhao, Sheng Fang, Ting Ji, Qian Ji, Wei-Long Zheng, Bao-Liang Lu:
Emotion Annotation Using Hierarchical Aligned Cluster Analysis. ICONIP (4) 2017: 572-580 - [c144]Hao Tang, Wei Liu, Wei-Long Zheng, Bao-Liang Lu:
Multimodal Emotion Recognition Using Deep Neural Networks. ICONIP (4) 2017: 811-819 - [c143]