| 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 | 92 | 2019 |
| 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 | 55 | 2020 |
| 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 | 45 | 2021 |
| 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 53 (11), 6776-6787, 2022 | 20 | 2022 |
| 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 | 11 | 2020 |
| Kpsnet: Keypoint detection and feature extraction for point cloud registration A Du, X Huang, J Zhang, L Yao, Q Wu 2019 IEEE International Conference on Image Processing (ICIP), 2576-2580, 2019 | 9 | 2019 |
| PCL: Point Contrast and Labeling for Weakly Supervised Point Cloud Semantic Segmentation A Du, T Zhou, S Pang, Q Wu, J Zhang IEEE Transactions on Multimedia, 2024 | 8 | 2024 |
| 2D medical image segmentation via learning multi-scale contextual dependencies S Pang, A Du, Z Yu, MA Orgun Methods 202, 40-53, 2022 | 7 | 2022 |
| 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 | 6 | 2020 |
| 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 | 5 | 2020 |
| 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 |
| A Multimodal Adversarial Database: Towards A Comprehensive Assessment of Adversarial Attacks and Defenses on Medical Images J Hu, Y He, W Zhang, S Pang, R Ma, A Du 2023 IEEE 10th International Conference on Data Science and Advanced …, 2023 | 1 | 2023 |
| Research on Point Cloud Segmentation and 3D Scene Understanding A Du PQDT-Global, 2022 | 1 | 2022 |
| Fine-grained tumor segmentation on computed tomography slices by leveraging bottom-up and top-down strategies Z Yu, S Pang, A Du, MA Orgun, Y Wang, H Lin Medical Imaging 2020: Image Processing 11313, 59-65, 2020 | 1 | 2020 |
| ADDM: Adversarial Defenses with Diffusion Model for Medical Imaging Data Mining Y He, S Pang, A Du, H Chen, L Cong, M Orgun International Conference on Advanced Data Mining and Applications, 78-93, 2024 | | 2024 |
| Dynamic Multimodal Prompt Tuning: Boost Few-Shot Learning with VLM-Guided Point Cloud Models X Gu, S Pang, A Du, Y Wang, J Miao, J Díez European Conference on Artificial Intelligence, 2024 | | 2024 |
| TriEn-Net: Non-parametric Representation Learning for Large-Scale Point Cloud Semantic Segmentation Y Wang, J Miao, A Du, X Gu, S Pang Chinese Conference on Pattern Recognition and Computer Vision (PRCV), 417-430, 2024 | | 2024 |
| MAFFN-SAT: 3D Point Cloud Defense via Multi-view Adaptive Feature Fusion and Smooth Adversarial Training S Zhang, A Du, J Zhang, Y Gao, S Pang IEEE Transactions on Geoscience and Remote Sensing, 2024 | | 2024 |
| Point-Level Label-Free Segmentation Framework for 3D Point Cloud Semantic Mining A Du, S Pang, M Orgun International Conference on Advanced Data Mining and Applications, 417-430, 2023 | | 2023 |
