Multi-instance multi-label learning with weak label SJ Yang, Y Jiang, ZH Zhou Proceedings of the Twenty-Third international joint conference on Artificial …, 2013 | 61 | 2013 |
Superpixel-guided discriminative low-rank representation of hyperspectral images for classification S Yang, J Hou, Y Jia, S Mei, Q Du IEEE Transactions on Image Processing 30, 8823-8835, 2021 | 33 | 2021 |
Hyperspectral image classification via sparse representation with incremental dictionaries S Yang, J Hou, Y Jia, S Mei, Q Du IEEE Geoscience and Remote Sensing Letters 17 (9), 1598-1602, 2019 | 12 | 2019 |
Pseudolabel guided kernel learning for hyperspectral image classification S Yang, J Hou, Y Jia, S Mei, Q Du IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2019 | 9 | 2019 |
Spectral reweighting and spectral similarity weighting for sparse hyperspectral unmixing D Zhang, T Wang, S Yang, Y Jia, F Li IEEE Geoscience and Remote Sensing Letters 19, 1-5, 2022 | 6 | 2022 |
Serendipity-driven celebrity video hyperlinking S Yang, L Pang, CW Ngo, B Huet Proceedings of the 2016 ACM on International Conference on Multimedia …, 2016 | 6 | 2016 |
Superpixelwise low-rank approximation-based partial label learning for hyperspectral image classification S Yang, Y Zhang, Y Ding, D Hong IEEE Geoscience and Remote Sensing Letters 20, 1-5, 2023 | 5 | 2023 |
Local low-rank approximation with superpixel-guided locality preserving graph for hyperspectral image classification S Yang, Y Zhang, Y Jia, W Zhang IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2022 | 5 | 2022 |
Unlabeled Data Guided Partial Label Learning for Hyperspectral Image Classification S Yang, Y Jia, Y Ding, X Wu, D Hong IEEE Geoscience and Remote Sensing Letters 21, 1-5, 2024 | 3 | 2024 |
S2GFormer: A Transformer and Graph Convolution Combing Framework for Hyperspectral Image Classification S Huang, Y Ding, Z Zhang, A Yang, S Yang, Y Cai, WW Cai IEEE Transactions on Geoscience and Remote Sensing, 2024 | 1 | 2024 |
Personalized Federated Learning with Local Attention S Liang, J Tian, S Yang, Y Zhang arXiv preprint arXiv:2304.01783, 2023 | | 2023 |