Progressive attention guided recurrent network for salient object detection X Zhang, T Wang, J Qi, H Lu, G Wang Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 700 | 2018 |
A Stagewise Refinement Model for Detecting Salient Objects in Images T Wang, A Borji, L Zhang, P Zhang, H Lu Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017 | 491 | 2017 |
Detect globally, refine locally: A novel approach to saliency detection T Wang, L Zhang, S Wang, H Lu, G Yang, X Ruan, A Borji Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 472 | 2018 |
Deep learning for light field saliency detection T Wang, Y Piao, X Li, L Zhang, H Lu Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 108 | 2019 |
Kernelized subspace ranking for saliency detection T Wang, L Zhang, H Lu, C Sun, J Qi Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016 | 103 | 2016 |
Referring expression object segmentation with caption-aware consistency YW Chen, YH Tsai, T Wang, YY Lin, MH Yang arXiv preprint arXiv:1910.04748, 2019 | 81 | 2019 |
Edge-aware convolution neural network based salient object detection W Guan, T Wang, J Qi, L Zhang, H Lu IEEE Signal Processing Letters 26 (1), 114-118, 2018 | 54 | 2018 |
A multistage refinement network for salient object detection L Zhang, J Wu, T Wang, A Borji, G Wei, H Lu IEEE Transactions on image Processing 29, 3534-3545, 2020 | 48 | 2020 |
Video matting via consistency-regularized graph neural networks T Wang, S Liu, Y Tian, K Li, MH Yang Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 27 | 2021 |
Multi-scale pyramid pooling network for salient object detection A Dakhia, T Wang, H Lu Neurocomputing 333, 211-220, 2019 | 22 | 2019 |
Visual saliency detection via kernelized subspace ranking with active learning L Zhang, J Sun, T Wang, Y Min, H Lu IEEE Transactions on Image Processing 29, 2258-2270, 2019 | 16 | 2019 |
A hybrid-backward refinement model for salient object detection A Dakhia, T Wang, H Lu Neurocomputing 358, 72-80, 2019 | 13 | 2019 |
Deep multi-level networks with multi-task learning for saliency detection L Zhang, X Fang, H Bo, T Wang, H Lu Neurocomputing 312, 229-238, 2018 | 10 | 2018 |
The logistic regression from the viewpoint of the factor space theory Q Cheng, T Wang, S Guo, D Zhang, K Jing, L Feng, Z Zhao, P Wang International Journal of Computers Communications & Control 12 (4), 492-502, 2017 | 10 | 2017 |
Influence of the Tikhonov regularization parameter on the accuracy of the inverse problem in electrocardiography T Wang, J Karel, P Bonizzi, RLM Peeters Sensors 23 (4), 1841, 2023 | 5 | 2023 |
ECGI with a deep neural network and 2D normalized body surface potential maps T Wang, P Bonizzi, J Karel, R Peeters 2021 Computing in Cardiology (CinC) 48, 1-4, 2021 | 2 | 2021 |
Factor space is the adaptive and deepening theory of fuzzy sets H Liu, R Wan, S Xue, T Wang, S Guo, J He 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 1-8, 2020 | 2 | 2020 |
Standardized 2D atrial mapping and its clinical applications T Wang, J Karel, E Invers-Rubio, I Hernández-Romero, R Peeters, ... Computers in Biology and Medicine 168, 107755, 2024 | 1 | 2024 |
Reconstruction of electrograms using a deep learning network trained on simulation data F Rehburg, R Peeters, T Wang, PM van Dam, P Bonizzi, J Karel Electrocardiographic Imaging Summit 2023, 2023 | | 2023 |