| Deep learning for visual understanding: A review Y Guo, Y Liu, A Oerlemans, S Lao, S Wu, MS Lew Neurocomputing 187, 27-48, 2016 | 2029 | 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 | 466 | 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 | 142 | 2017 |
| Learning relaxed deep supervision for better edge detection Y Liu, MS Lew Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 120 | 2016 |
| 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 | 119 | 2018 |
| A survey of traditional and deep learning-based feature descriptors for high dimensional data in computer vision T Georgiou, Y Liu, W Chen, M Lew International Journal of Multimedia Information Retrieval 9 (3), 135-170, 2020 | 77 | 2020 |
| A Simple Convolutional Neural Network for Accurate P300 Detection and Character Spelling in Brain Computer Interface. H Shan, Y Liu, TP Stefanov IJCAI, 1604-1610, 2018 | 51 | 2018 |
| 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 | 50 | 2015 |
| Learning fluid flows T Georgiou, S Schmitt, M Olhofer, Y Liu, T Bäck, M Lew 2018 International Joint Conference on Neural Networks (IJCNN), 1-8, 2018 | 43 | 2018 |
| Swapgan: A multistage generative approach for person-to-person fashion style transfer Y Liu, W Chen, L Liu, MS Lew IEEE Transactions on Multimedia 21 (9), 2209-2222, 2019 | 42 | 2019 |
| Hierarchical projective invariant contexts for shape recognition Q Jia, X Fan, Y Liu, H Li, Z Luo, H Guo Pattern Recognition 52, 358-374, 2016 | 40 | 2016 |
| More classifiers, less forgetting: A generic multi-classifier paradigm for incremental learning Y Liu, S Parisot, G Slabaugh, X Jia, A Leonardis, T Tuytelaars Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 34 | 2020 |
| Dual gaussian-based variational subspace disentanglement for visible-infrared person re-identification N Pu, W Chen, Y Liu, EM Bakker, MS Lew Proceedings of the 28th ACM International Conference on Multimedia, 2149-2158, 2020 | 31 | 2020 |
| Lifelong person re-identification via adaptive knowledge accumulation N Pu, W Chen, Y Liu, EM Bakker, MS Lew Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 30 | 2021 |
| 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 | 29 | 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 | 20 | 2018 |
| On the exploration of convolutional fusion networks for visual recognition Y Liu, Y Guo, M S. Lew MultiMedia Modeling: 23rd International Conference, MMM 2017, Reykjavik …, 2016 | 20 | 2016 |
| 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 | 19 | 2018 |
| Integrating information theory and adversarial learning for cross-modal retrieval W Chen, Y Liu, EM Bakker, MS Lew Pattern Recognition 117, 107983, 2021 | 18 | 2021 |
| Feature estimations based correlation distillation for incremental image retrieval W Chen, Y Liu, N Pu, W Wang, L Liu, MS Lew IEEE Transactions on Multimedia 24, 1844-1856, 2021 | 18 | 2021 |
Michael LewLeiden UniversityVerified email at liacs.nl
