| Deep learning for visual understanding: A review Y Guo, Y Liu, A Oerlemans, S Lao, S Wu, MS Lew Neurocomputing 187, 27-48, 2016 | 2915 | 2016 |
| A review of semantic segmentation using deep neural networks Y Guo, Y Liu, T Georgiou, MS Lew International journal of multimedia information retrieval 7, 87-93, 2018 | 920 | 2018 |
| Learning a recurrent residual fusion network for multimodal matching Y Liu, Y Guo, EM Bakker, MS Lew Proceedings of the IEEE international conference on computer vision, 4107-4116, 2017 | 180 | 2017 |
| CNN-RNN: a large-scale hierarchical image classification framework Y Guo, Y Liu, EM Bakker, Y Guo, MS Lew Multimedia tools and applications 77 (8), 10251-10271, 2018 | 174 | 2018 |
| Chinese named entity recognition: The state of the art P Liu, Y Guo, F Wang, G Li Neurocomputing 473, 37-53, 2022 | 154 | 2022 |
| Colloidal chemically fabricated ZnO: Cu-based photodetector with extended UV-visible detection waveband L Hu, L Zhu, H He, Y Guo, G Pan, J Jiang, Y Jin, L Sun, Z Ye Nanoscale 5 (20), 9577-9581, 2013 | 72 | 2013 |
| Deepindex for accurate and efficient image retrieval Y Liu, Y Guo, S Wu, MS Lew Proceedings of the 5th ACM on International Conference on Multimedia …, 2015 | 55 | 2015 |
| CycleMatch: A cycle-consistent embedding network for image-text matching Y Liu, Y Guo, L Liu, EM Bakker, MS Lew Pattern Recognition 93, 365-379, 2019 | 44 | 2019 |
| Learning visual and textual representations for multimodal matching and classification Y Liu, L Liu, Y Guo, MS Lew Pattern Recognition 84, 51-67, 2018 | 35 | 2018 |
| Cross-modal multistep fusion network with co-attention for visual question answering M Lao, Y Guo, H Wang, X Zhang IEEE Access 6, 31516-31524, 2018 | 35 | 2018 |
| Fusion that matters: convolutional fusion networks for visual recognition Y Liu, Y Guo, T Georgiou, MS Lew Multimedia Tools and Applications 77, 29407-29434, 2018 | 30 | 2018 |
| On the exploration of convolutional fusion networks for visual recognition Y Liu, Y Guo, M S. Lew International conference on multimedia modeling, 277-289, 2016 | 23 | 2016 |
| From superficial to deep: Language bias driven curriculum learning for visual question answering M Lao, Y Guo, Y Liu, W Chen, N Pu, MS Lew Proceedings of the 29th ACM International Conference on Multimedia, 3370-3379, 2021 | 22 | 2021 |
| Multi-stage hybrid embedding fusion network for visual question answering M Lao, Y Guo, N Pu, W Chen, Y Liu, MS Lew Neurocomputing 423, 541-550, 2021 | 20 | 2021 |
| Deep learning for video-text retrieval: a review C Zhu, Q Jia, W Chen, Y Guo, Y Liu International Journal of Multimedia Information Retrieval 12 (1), 3, 2023 | 19 | 2023 |
| A language prior based focal loss for visual question answering M Lao, Y Guo, Y Liu, MS Lew 2021 IEEE International Conference on Multimedia and Expo (ICME), 1-6, 2021 | 19 | 2021 |
| Combining convolutional neural network and photometric refinement for accurate homography estimation L Kang, Y Wei, Y Xie, J Jiang, Y Guo IEEE Access 7, 109460-109473, 2019 | 15 | 2019 |
| Bag of surrogate parts feature for visual recognition Y Guo, Y Liu, S Lao, EM Bakker, L Bai, MS Lew IEEE Transactions on Multimedia 20 (6), 1525-1536, 2017 | 13 | 2017 |
| Bag of Surrogate Parts: one inherent feature of deep CNNs. Y Guo, MS Lew BMVC, 2016 | 12 | 2016 |
| FCT: fusing CNN and transformer for scene classification Y Xie, J Yan, L Kang, Y Guo, J Zhang, X Luan International Journal of Multimedia Information Retrieval 11 (4), 611-618, 2022 | 11 | 2022 |