| Deep multimodal multilinear fusion with high-order polynomial pooling M Hou, J Tang, J Zhang, W Kong, Q Zhao Advances in Neural Information Processing Systems 32, 2019 | 120 | 2019 |
| CTFN: Hierarchical learning for multimodal sentiment analysis using coupled-translation fusion network J Tang, K Li, X Jin, A Cichocki, Q Zhao, W Kong Proceedings of the 59th Annual Meeting of the Association for Computational …, 2021 | 69 | 2021 |
| Dynamically adjust word representations using unaligned multimodal information J Guo, J Tang, W Dai, Y Ding, W Kong Proceedings of the 30th ACM international conference on multimedia, 3394-3402, 2022 | 41 | 2022 |
| BAFN: Bi-direction attention based fusion network for multimodal sentiment analysis J Tang, D Liu, X Jin, Y Peng, Q Zhao, Y Ding, W Kong IEEE Transactions on Circuits and Systems for Video Technology 33 (4), 1966-1978, 2022 | 40 | 2022 |
| EEG-based sleep staging analysis with functional connectivity H Huang, J Zhang, L Zhu, J Tang, G Lin, W Kong, X Lei, L Zhu Sensors 21 (6), 1988, 2021 | 40 | 2021 |
| A multi-stage dynamical fusion network for multimodal emotion recognition S Chen, J Tang, L Zhu, W Kong Cognitive Neurodynamics 17 (3), 671-680, 2023 | 27 | 2023 |
| CTNN: A convolutional tensor-train neural network for multi-task brainprint recognition X Jin, J Tang, X Kong, Y Peng, J Cao, Q Zhao, W Kong IEEE Transactions on Neural Systems and Rehabilitation Engineering 29, 103-112, 2020 | 25 | 2020 |
| MMT: Multi-way Multi-modal Transformer for Multimodal Learning. J Tang, K Li, M Hou, X Jin, W Kong, Y Ding, Q Zhao IJCAI, 3458-3465, 2022 | 17 | 2022 |
| Emotional-state brain network analysis revealed by minimum spanning tree using EEG signals J Zhang, S Zhao, G Yang, J Tang, T Zhang, Y Peng, W Kong 2018 IEEE international conference on bioinformatics and biomedicine (BIBM …, 2018 | 4 | 2018 |
| Disentangled Adversarial Generalization Network for cross-session Task-independent Brainprint Recognition X Jin, N Li, W Kong, Q Zhao, J Tang, L Zhu, J Cao IEEE Transactions on Cognitive and Developmental Systems, 2023 | 2 | 2023 |
| PSPN: Pseudo-Siamese Pyramid Network for multimodal emotion analysis Y Yin, W Kong, J Tang, J Li, F Babiloni Cognitive Neurodynamics, 1-14, 2024 | 1 | 2024 |
| Tree-Based Mix-Order Polynomial Fusion Network for Multimodal Sentiment Analysis J Tang, M Hou, X Jin, J Zhang, Q Zhao, W Kong Systems 11 (1), 44, 2023 | 1 | 2023 |
| Emotion Recognition Using Multi-core Tensor Learning and Multimodal Physiological Signal H Xu, J Tang, J Zhang, L Zhu International Workshop on Human Brain and Artificial Intelligence, 137-148, 2021 | 1 | 2021 |
| Joint disentangled representation and domain adversarial training for EEG-based cross-session biometric recognition in single-task protocols H Liu, X Jin, D Liu, W Kong, J Tang, Y Peng Cognitive Neurodynamics 19 (1), 31, 2025 | | 2025 |
| Brain-Eye Collaboration Target Detection and Localization in Remote Sensing Image J Han, L Ma, L Zhu, J Tang, W Kong IEEE Transactions on Cognitive and Developmental Systems, 2025 | | 2025 |
| MECG: modality-enhanced convolutional graph for unbalanced multimodal representations J Tang, B Ni, Y Yang, Y Ding, W Kong The Journal of Supercomputing 81 (1), 319, 2025 | | 2025 |
| Visual guided Dual-spatial Interaction Network for Fine-grained Brain Semantic Decoding J Tang, Y Yang, Q Zhao, Y Ding, J Zhang, Y Song, W Kong IEEE Transactions on Instrumentation and Measurement, 2024 | | 2024 |
| Cross-session brainprint recognition method based on tensorized spatial-frequency attention network (tsfan) with domain adaptation K Wanzeng, X Jin, X Yang, L Zhu, T Jiajia US Patent App. 18/223,623, 2024 | | 2024 |
| Multimodal Sarcasm Analysis: Sarcastic Cues Capture from Both Emotional Polarity and Semantic Information Z Yang, J Tang, F Zhou, T Toya, K Ozawa, W Kong IEICE Conferences Archives, 2024 | | 2024 |
| Fine-grained Dual-space Context Analysis Network for Multimodal Emotion Recognition J Li, J Tang, W Kong, Y Ying 2024 International Joint Conference on Neural Networks (IJCNN), 1-8, 2024 | | 2024 |
wanzeng kongProf. College of Computer Science, Hangzhou Dianzi University確認したメール アドレス: hdu.edu.cn
