| Multimodal Affective Analysis Using Hierarchical Attention Strategy with Word-Level Alignment Y Gu, K Yang, S Fu, S Chen, X Li, I Marsic Proceedings of the 56th Annual Meeting of the Association for Computational …, 2018 | 170 | 2018 |
| Behavioral and physiological signals-based deep multimodal approach for mobile emotion recognition K Yang, C Wang, Y Gu, Z Sarsenbayeva, B Tag, T Dingler, G Wadley, ... IEEE Transactions on Affective Computing 14 (2), 1082-1097, 2021 | 75 | 2021 |
| Hybrid attention based multimodal network for spoken language classification Y Gu, K Yang, S Fu, S Chen, X Li, I Marsic Proceedings of the Conference. association for Computational Linguistics …, 2018 | 73 | 2018 |
| Speech intention classification with multimodal deep learning Y Gu, X Li, S Chen, J Zhang, I Marsic Advances in Artificial Intelligence: 30th Canadian Conference on Artificial …, 2017 | 65 | 2017 |
| Deep Multimodal Learning for Emotion Recognition in Spoken Language Y Gu, S Chen, I Marsic 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 60 | 2018 |
| Human conversation analysis using attentive multimodal networks with hierarchical encoder-decoder Y Gu, X Li, K Huang, S Fu, K Yang, S Chen, M Zhou, I Marsic Proceedings of the 26th ACM international conference on Multimedia, 537-545, 2018 | 41 | 2018 |
| Mutual correlation attentive factors in dyadic fusion networks for speech emotion recognition Y Gu, X Lyu, W Sun, W Li, S Chen, X Li, I Marsic Proceedings of the 27th ACM International Conference on Multimedia, 157-166, 2019 | 34 | 2019 |
| Mobile emotion recognition via multiple physiological signals using convolution-augmented transformer K Yang, B Tag, Y Gu, C Wang, T Dingler, G Wadley, J Goncalves Proceedings of the 2022 International Conference on Multimedia Retrieval …, 2022 | 26 | 2022 |
| Progress estimation and phase detection for sequential processes X Li, Y Zhang, J Zhang, M Zhou, S Chen, Y Gu, Y Chen, I Marsic, ... Proceedings of the ACM on interactive, mobile, wearable and ubiquitous …, 2017 | 19 | 2017 |
| Residual recurrent neural network for speech enhancement J Abdulbaqi, Y Gu, S Chen, I Marsic ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 18 | 2020 |
| Survey on emotion sensing using mobile devices K Yang, B Tag, C Wang, Y Gu, Z Sarsenbayeva, T Dingler, G Wadley, ... IEEE Transactions on Affective Computing 14 (4), 2678-2696, 2022 | 16 | 2022 |
| Multimodal attention network for trauma activity recognition from spoken language and environmental sound Y Gu, R Zhang, X Zhao, S Chen, J Abdulbaqi, I Marsic, M Cheng, RS Burd 2019 IEEE International Conference on Healthcare Informatics (ICHI), 1-6, 2019 | 14 | 2019 |
| Language-based process phase detection in the trauma resuscitation Y Gu, X Li, S Chen, H Li, RA Farneth, I Marsic, RS Burd 2017 IEEE International Conference on Healthcare Informatics (ICHI), 239-247, 2017 | 14 | 2017 |
| Speech-based activity recognition for trauma resuscitation J Abdulbaqi, Y Gu, Z Xu, C Gao, I Marsic, RS Burd 2020 IEEE International Conference on Healthcare Informatics (ICHI), 1-8, 2020 | 9 | 2020 |
| RHR-Net: A residual hourglass recurrent neural network for speech enhancement J Abdulbaqi, Y Gu, I Marsic arXiv preprint arXiv:1904.07294, 2019 | 9 | 2019 |
| On-device constrained self-supervised speech representation learning for keyword spotting via knowledge distillation GP Yang, Y Gu, Q Tang, D Du, Y Liu arXiv preprint arXiv:2307.02720, 2023 | 7 | 2023 |
| Self-supervised speech representation learning for keyword-spotting with light-weight transformers C Gao, Y Gu, F Caliva, Y Liu ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 6 | 2023 |
| Video-based concurrent activity recognition for trauma resuscitation Y Zhang, Y Gu, I Marsic, Y Zheng, RS Burd 2020 IEEE International Conference on Healthcare Informatics (ICHI), 1-6, 2020 | 3 | 2020 |
| Process progress estimation and phase detection X Li, Y Zhang, J Zhang, Y Chen, S Chen, Y Gu, M Zhou, RA Farneth, ... CoRR, 2017 | 2 | 2017 |
| On-device constrained self-supervised learning for keyword spotting via quantization aware pre-training and fine-tuning GP Yang, Y Gu, S Macha, Q Tang, Y Liu ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and …, 2024 | 1 | 2024 |
Ivan MarsicRutgers University, Department of Electrical and Computer EngineeringZweryfikowany adres z rutgers.edu