Ling Huang

According to our database, Ling Huang authored at least 39 papers between 2017 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Towards Accurate and Reliable ICU Outcome Prediction: A Multimodal Learning Framework Based on Belief Function Theory using Structured EHRs and Free-Text Notes.

Yucheng Ruan, Daniel J. Tan, See-Kiong Ng, Ling Huang, Mengling Feng

J. Heal. Informatics Res., June, 2026

Bridging the Modality Bottleneck in Pathology MIL through Virtual Molecular Staining.

Yucheng Xing, Pei Liu, Jingying Ma, Ruping Hong, Jiangdong Qiu, Tianyu Liu, Kai He, Ling Huang, Mengling Feng

CoRR, May, 2026

Beyond Semantics: An Evidential Reasoning-Aware Multi-View Learning Framework for Trustworthy Mental Health Prediction.

Yucheng Ruan, Ling Huang, Qika Lin, Kai He, Mengling Feng

CoRR, May, 2026

EsurvFusion: An Evidential Multimodal Survival Fusion Model Based on Epistemic Random Fuzzy Sets.

Ling Huang, Yucheng Xing, Qika Lin, Jinming Duan, Su Ruan, Mengling Feng

IEEE Trans. Fuzzy Syst., January, 2026

Domain-continual learning for multi-center anatomical detection via prompt-enhanced and densely-fused MedSAM.

Zhan Gao, Ling Huang, Qika Lin, Bin Pu, Kai He, Mengling Feng, Kenli Li

Inf. Fusion, 2026

A hierarchical teacher-student learning framework with adaptive cross-modal fusion for brain tumor segmentation.

Tongxue Zhou, Su Ruan, Jinming Duan, Haigen Hu, Yanda Meng, Ling Huang, Defu Yang, Bingbing Jiang, Tingjin Luo, Zhiwei Ji, Baiying Lei

Expert Syst. Appl., 2026

2025

Toward Reliable Medical Image Segmentation by Modeling Evidential Calibrated Uncertainty.

Ke Zou, Yidi Chen, Ling Huang, Nan Zhou, Xuedong Yuan, Xiaojing Shen, Meng Wang, Rick Siow Mong Goh, Yong Liu, Yih Chung Tham, Huazhu Fu

IEEE Trans. Cybern., December, 2025

DPsurv: Dual-Prototype Evidential Fusion for Uncertainty-Aware and Interpretable Whole-Slide Image Survival Prediction.

Yucheng Xing, Ling Huang, Jingying Ma, Ruping Hong, Jiangdong Qiu, Pei Liu, Kai He, Huazhu Fu, Mengling Feng

CoRR, October, 2025

A Foundation Model for Chest X-ray Interpretation with Grounded Reasoning via Online Reinforcement Learning.

Qika Lin, Yifan Zhu, Bin Pu, Ling Huang, Haoran Luo, Jingying Ma, Zhen Peng, Tianzhe Zhao, Fangzhi Xu, Jian Zhang, Kai He, Zhonghong Ou, Swapnil Mishra, Mengling Feng

CoRR, September, 2025

Evidence-based multimodal fusion on structured EHRs and free-text notes for ICU outcome prediction.

Yucheng Ruan, Daniel J. Tan, See-Kiong Ng, Ling Huang, Mengling Feng

CoRR, January, 2025

Adversarial example detection and defense based on the evidence consistency from Dempster-Shafer layers.

Yue Xu, Yibo Qiu, Ling Huang, Rui Wang, Lunde Chen, Jiwen Zhou, Wanyu Liu

Knowl. Based Syst., 2025

Has multimodal learning delivered universal intelligence in healthcare? A comprehensive survey.

Qika Lin, Yifan Zhu, Xin Mei, Ling Huang, Jingying Ma, Kai He, Zhen Peng, Erik Cambria, Mengling Feng

Inf. Fusion, 2025

Deep evidential fusion with uncertainty quantification and reliability learning for multimodal medical image segmentation.

Ling Huang, Su Ruan, Pierre Decazes, Thierry Denoeux

Inf. Fusion, 2025

Evidential time-to-event prediction with calibrated uncertainty quantification.

Ling Huang, Yucheng Xing, Swapnil Mishra, Thierry Denoeux, Mengling Feng

Int. J. Approx. Reason., 2025

Self-supervised Quantized Representation for Seamlessly Integrating Knowledge Graphs with Large Language Models.

Qika Lin, Tianzhe Zhao, Kai He, Zhen Peng, Fangzhi Xu, Ling Huang, Jingying Ma, Mengling Feng

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

2024

A review of uncertainty quantification in medical image analysis: Probabilistic and non-probabilistic methods.

Ling Huang, Su Ruan, Yucheng Xing, Mengling Feng

Medical Image Anal., 2024

EsurvFusion: An evidential multimodal survival fusion model based on Gaussian random fuzzy numbers.

Ling Huang, Yucheng Xing, Qika Lin, Su Ruan, Mengling Feng

CoRR, 2024

Evidential time-to-event prediction model with well-calibrated uncertainty estimation.

Ling Huang, Yucheng Xing, Swapnil Mishra, Thierry Denoeux, Mengling Feng

CoRR, 2024

An Evidence-Based Framework For Heterogeneous Electronic Health Records: A Case Study In Mortality Prediction.

Yucheng Ruan, Ling Huang, Qianyi Xu, Mengling Feng

Proceedings of the Belief Functions: Theory and Applications, 2024

An Evidential Time-to-Event Prediction Model Based on Gaussian Random Fuzzy Numbers.

Ling Huang, Yucheng Xing, Thierry Denoeux, Mengling Feng

Proceedings of the Belief Functions: Theory and Applications, 2024

2023

Medical image segmentation with belief function theory and deep learning. (Segmentation d'images médicales avec la théorie de la fonction de croyance et l'apprentissage en profondeur).

Ling Huang

PhD thesis, 2023

Application of belief functions to medical image segmentation: A review.

Ling Huang, Su Ruan, Thierry Denoeux

Inf. Fusion, 2023

Semi-supervised multiple evidence fusion for brain tumor segmentation.

Ling Huang, Su Ruan, Thierry Denoeux

Neurocomputing, 2023

Deep evidential fusion with uncertainty quantification and contextual discounting for multimodal medical image segmentation.

Ling Huang, Su Ruan, Pierre Decazes, Thierry Denoeux

CoRR, 2023

Medical Image Segmentation with Belief Function Theory and Deep Learning.

Ling Huang

CoRR, 2023

2022

Unsupervised adversarial image retrieval.

Ling Huang, Cong Bai, Yijuan Lu, Shaobo Zhang, Shengyong Chen

Multim. Syst., 2022

Lymphoma segmentation from 3D PET-CT images using a deep evidential network.

Ling Huang, Su Ruan, Pierre Decazes, Thierry Denoeux

Int. J. Approx. Reason., 2022

Application of belief functions to medical image segmentation: A review.

Ling Huang, Su Ruan

CoRR, 2022

Evidence Fusion with Contextual Discounting for Multi-modality Medical Image Segmentation.

Ling Huang, Thierry Denoeux, Pierre Vera, Su Ruan

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

2021

Unsupervised Adversarial Instance-Level Image Retrieval.

Cong Bai, Hongkai Li, Jinglin Zhang, Ling Huang, Lu Zhang

IEEE Trans. Multim., 2021

Deep PET/CT Fusion with Dempster-Shafer Theory for Lymphoma Segmentation.

Ling Huang, Thierry Denoeux, David Tonnelet, Pierre Decazes, Su Ruan

Proceedings of the Machine Learning in Medical Imaging - 12th International Workshop, 2021

Belief Function-Based Semi-Supervised Learning For Brain Tumor Segmentation.

Ling Huang, Su Ruan, Thierry Denoeux

Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021

Covid-19 Classification with Deep Neural Network and Belief Functions.

Ling Huang, Su Ruan, Thierry Denoeux

Proceedings of the BIBE 2021: The Fifth International Conference on Biological Information and Biomedical Engineering, 2021

Evidential Segmentation of 3D PET/CT Images.

Ling Huang, Su Ruan, Pierre Decazes, Thierry Denoeux

Proceedings of the Belief Functions: Theory and Applications, 2021

2020

Instance Image Retrieval with Generative Adversarial Training.

Hongkai Li, Cong Bai, Ling Huang, Yu-Gang Jiang, Shengyong Chen

Proceedings of the MultiMedia Modeling - 26th International Conference, 2020

2019

Adversarial Learning for Content-Based Image Retrieval.

Ling Huang, Cong Bai, Yijuan Lu, Shengyong Chen, Qi Tian

Proceedings of the 2nd IEEE Conference on Multimedia Information Processing and Retrieval, 2019

2018

Saliency-based multi-feature modeling for semantic image retrieval.

Cong Bai, Jianan Chen, Ling Huang, Kidiyo Kpalma, Shengyong Chen

J. Vis. Commun. Image Represent., 2018

Optimization of deep convolutional neural network for large scale image retrieval.

Cong Bai, Ling Huang, Xiang Pan, Jianwei Zheng, Shengyong Chen

Neurocomputing, 2018

2017

Visual Saliency Fusion Based Multi-feature for Semantic Image Retrieval.

Jianan Chen, Cong Bai, Ling Huang, Zhi Liu, Shengyong Chen

Proceedings of the Computer Vision - Second CCF Chinese Conference, 2017