| Optimization of deep convolutional neural network for large scale image retrieval C Bai, L Huang, X Pan, J Zheng, S Chen Neurocomputing 303, 60-67, 2018 | 129 | 2018 |
| Saliency-based multi-feature modeling for semantic image retrieval C Bai, J Chen, L Huang, K Kpalma, S Chen Journal of Visual Communication and Image Representation 50, 199-204, 2018 | 61 | 2018 |
| Optimization of deep convolutional neural network for large scale image classification 白琮， 黄玲， 陈佳楠， 潘翔， 陈胜勇 Journal of Software 29 (4), 1029-1038, 2017 | 48* | 2017 |
| Unsupervised adversarial instance-level image retrieval C Bai, H Li, J Zhang, L Huang, L Zhang IEEE Transactions on Multimedia 23, 2199-2207, 2021 | 43 | 2021 |
| Lymphoma segmentation from 3D PET-CT images using a deep evidential network L Huang, S Ruan, P Decazes, T Denoeux International Journal of Approximate Reasoning 149, 39-60, 2022 | 40 | 2022 |
| Belief function-based semi-supervised learning for brain tumor segmentation L Huang, S Ruan, T Denoeux ISBI2021, 2021 | 27 | 2021 |
| Covid-19 classification with deep neural network and belief functions L Huang, S Ruan, T Denoeux BIBE2021, 2021 | 27 | 2021 |
| Evidence fusion with contextual discounting for multi-modality medical image segmentation L Huang, T Denoeux, P Vera, S Ruan MICCAI2022, 2022 | 26 | 2022 |
| Application of belief functions to medical image segmentation: A review L Huang, S Ruan, T Denoeux Information Fusion 91, 737-756, 2023 | 25 | 2023 |
| Deep PET/CT fusion with Dempster-Shafer theory for lymphoma segmentation L Huang, T Denoeux, D Tonnelet, P Decazes, S Ruan MICCAI 2021 workshop MLMI, 2021 | 19 | 2021 |
| Evidential segmentation of 3D PET/CT images L Huang, S Ruan, P Decazes, T Denoeux BELIEF2021, 2021 | 16 | 2021 |
| Semi-supervised multiple evidence fusion for brain tumor segmentation L Huang, S Ruan, T Denœux Neurocomputing 535, 40-52, 2023 | 13 | 2023 |
| A review of uncertainty quantification in medical image analysis: probabilistic and non-probabilistic methods L Huang, S Ruan, Y Xing, M Feng Medical Image Analysis, 103223, 2024 | 8 | 2024 |
| Adversarial learning for content-based image retrieval L Huang, C Bai, Y Lu, S Chen, Q Tian 2019 IEEE Conference on Multimedia Information Processing and Retrieval …, 2019 | 7 | 2019 |
| Instance image retrieval with generative adversarial training H Li, C Bai, L Huang, Y Jiang, S Chen MultiMedia Modeling: 26th International Conference, MMM 2020, Daejeon, South …, 2020 | 5 | 2020 |
| Unsupervised adversarial image retrieval L Huang, C Bai, Y Lu, S Zhang, S Chen Multimedia Systems, 1-13, 2022 | 4 | 2022 |
| Deep evidential fusion with uncertainty quantification and reliability learning for multimodal medical image segmentation L Huang, S Ruan, P Decazes, T Denœux Information Fusion 113, 102648, 2025 | 3* | 2025 |
| Has Multimodal Learning Delivered Universal Intelligence in Healthcare? A Comprehensive Survey Q Lin, Y Zhu, X Mei, L Huang, J Ma, K He, Z Peng, E Cambria, M Feng arXiv preprint arXiv:2408.12880, 2024 | | 2024 |
| An Evidence-Based Framework For Heterogeneous Electronic Health Records: A Case Study In Mortality Prediction Y Ruan, L Huang, Q Xu, M Feng International Conference on Belief Functions, 78-86, 2024 | | 2024 |
| An evidential time-to-event prediction model based on Gaussian random fuzzy numbers L Huang, Y Xing, T Denoeux, M Feng International Conference on Belief Functions, 49-57, 2024 | | 2024 |
Thierry DenoeuxProfessor, Université de technologie de Compiègne, Institut Universitaire de FranceVerified email at utc.fr
