| A novel end-to-end classifier using domain transferred deep convolutional neural networks for biomedical images S Pang, Z Yu, MA Orgun Computer methods and programs in biomedicine 140, 283-293, 2017 | 69 | 2017 |
| A novel fused convolutional neural network for biomedical image classification S Pang, A Du, MA Orgun, Z Yu Medical & biological engineering & computing 57 (1), 107-121, 2019 | 59 | 2019 |
| Deep learning to frame objects for visual target tracking S Pang, JJ del Coz, Z Yu, O Luaces, J Díez Engineering Applications of Artificial Intelligence 65, 406-420, 2017 | 36 | 2017 |
| A novel biomedical image indexing and retrieval system via deep preference learning S Pang, MA Orgun, Z Yu Computer methods and programs in biomedicine 158, 53-69, 2018 | 29 | 2018 |
| CTumorGAN: a unified framework for automatic computed tomography tumor segmentation S Pang, A Du, MA Orgun, Z Yu, Y Wang, Y Wang, G Liu European journal of nuclear medicine and molecular imaging 47 (10), 2248-2268, 2020 | 25 | 2020 |
| Incremental graph regulated nonnegative matrix factorization for face recognition ZZ Yu, YH Liu, B Li, SC Pang, CC Jia Journal of Applied Mathematics 2014, 2014 | 14 | 2014 |
| Fast and accurate lung tumor spotting and segmentation for boundary delineation on CT slices in a coarse-to-fine framework S Pang, A Du, X He, J Díez, MA Orgun International Conference on Neural Information Processing, 589-597, 2019 | 11 | 2019 |
| Deep learning and preference learning for object tracking: a combined approach S Pang, JJ Del Coz, Z Yu, O Luaces, J Díez Neural Processing Letters 47 (3), 859-876, 2018 | 10 | 2018 |
| Tumor attention networks: Better feature selection, better tumor segmentation S Pang, A Du, MA Orgun, Y Wang, Z Yu Neural Networks 140, 203-222, 2021 | 7 | 2021 |
| Combining deep learning and preference learning for object tracking S Pang, JJ Coz, Z Yu, O Luaces, J Díez International Conference on Neural Information Processing, 70-77, 2016 | 7 | 2016 |
| Face recognition: a novel deep learning approach SC Pang, ZZ Yu Journal of Optical Technology 82 (4), 237-245, 2015 | 6 | 2015 |
| Correlation matters: multi-scale fine-grained contextual information extraction for hepatic tumor segmentation S Pang, A Du, Z Yu, MA Orgun Pacific-Asia Conference on Knowledge Discovery and Data Mining, 462-474, 2020 | 5 | 2020 |
| Weakly supervised learning for image keypoint matching using graph convolutional networks S Pang, A Du, MA Orgun, H Chen Knowledge-Based Systems 197, 105871, 2020 | 4 | 2020 |
| Global and local information based spherical marginal fisher analysis for face recognition R Liu, C Jia, E Pang, M Qu, S Pang, Z Yu Journal of Information and Computational Science 10 (4), 1025-1034, 2013 | 4 | 2013 |
| Exploring long-short-term context for point cloud semantic segmentation A Du, S Pang, X Huang, J Zhang, Q Wu 2020 IEEE International Conference on Image Processing (ICIP), 2755-2759, 2020 | 3 | 2020 |
| Robust multi-object tracking using deep learning framework SC Pang, A Du, ZZ Yu Journal of Optical Technology 82 (8), 516-527, 2015 | 3 | 2015 |
| A new construction method of neighbor graph for locality preserving projections H Zheng, J Liu, C Wu, S Pang, E Pang, C Jia, Z Yu JOURNAL OF INFORMATION &COMPUTATIONAL SCIENCE 10 (5), 1357-1365, 2013 | 3 | 2013 |
| Leveraging deep preference learning for indexing and retrieval of biomedical images S Pang, MA Orgun, A Du, Z Yu 2017 8th International IEEE/EMBS Conference on Neural Engineering (NER), 126-129, 2017 | 2 | 2017 |
| 2D medical image segmentation via learning multi-scale contextual dependencies S Pang, A Du, Z Yu, MA Orgun Methods 202, 40-53, 2022 | 1 | 2022 |
| Tgnet: A Task-Guided Network Architecture for Multi-Organ and Tumour Segmentation from Partially Labelled Datasets H Wu, S Pang, A Sowmya 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI), 1-5, 2022 | 1 | 2022 |
