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 | 86 | 2017 |
A novel fused convolutional neural network for biomedical image classification S Pang, A Du, MA Orgun, Z Yu Medical & biological engineering & computing 57, 107-121, 2019 | 78 | 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 | 59 | 2017 |
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, 2248-2268, 2020 | 44 | 2020 |
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 | 39 | 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 | 36 | 2021 |
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 | 17 | 2014 |
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, 859-876, 2018 | 14 | 2018 |
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 Neural Information Processing: 26th International Conference, ICONIP 2019 …, 2019 | 13 | 2019 |
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 | 10 | 2020 |
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 | 9 | 2022 |
Training radiomics-based CNNs for clinical outcome prediction: Challenges, strategies and findings S Pang, M Field, J Dowling, S Vinod, L Holloway, A Sowmya Artificial Intelligence in Medicine 123, 102230, 2022 | 9 | 2022 |
Face recognition: a novel deep learning approach SC Pang, ZZ Yu Journal of Optical Technology 82 (4), 237-245, 2015 | 8 | 2015 |
Beyond CNNs: exploiting further inherent symmetries in medical image segmentation S Pang, A Du, MA Orgun, Y Wang, QZ Sheng, S Wang, X Huang, Z Yu IEEE Transactions on Cybernetics, 2022 | 7 | 2022 |
Combining deep learning and preference learning for object tracking S Pang, JJ Del Coz, Z Yu, O Luaces, J Díez International Conference on Neural Information Processing, 70-77, 2016 | 7 | 2016 |
2D medical image segmentation via learning multi-scale contextual dependencies S Pang, A Du, Z Yu, MA Orgun Methods 202, 40-53, 2022 | 6 | 2022 |
Correlation matters: multi-scale fine-grained contextual information extraction for hepatic tumor segmentation S Pang, A Du, Z Yu, MA Orgun Advances in Knowledge Discovery and Data Mining: 24th Pacific-Asia …, 2020 | 6 | 2020 |
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 | 5 | 2020 |
Robust multi-object tracking using deep learning framework SC Pang, A Du, ZZ Yu Journal of Optical Technology 82 (8), 516-527, 2015 | 4 | 2015 |
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 |