401 citations · 900 across the 16 of their papers we have counts for
16 papers
Calibrating Multimodal Learning
Huan Ma. Qingyang Zhang, Changqing Zhang, Bingzhe Wu +3
Multimodal machine learning has achieved remarkable progress in a wide range of scenarios. However, the reliability of multimodal learning remains largely unexplored. In this paper…
Uncertainty-inspired Open Set Learning for Retinal Anomaly Identification
Meng Wang, Tian Lin, Lianyu Wang +21
Failure to recognize samples from the classes unseen during training is a major limitation of artificial intelligence in the real-world implementation for recognition and classific…
Fairness-guided Few-shot Prompting for Large Language Models
Huan Ma, Changqing Zhang, Yatao Bian +7
Large language models have demonstrated surprising ability to perform in-context learning, i.e., these models can be directly applied to solve numerous downstream tasks by conditio…
Trusted Multi-View Classification with Dynamic Evidential Fusion
Zongbo Han, Changqing Zhang, Huazhu Fu +1
Existing multi-view classification algorithms focus on promoting accuracy by exploiting different views, typically integrating them into common representations for follow-up tasks.…
Uncertainty-Aware Multi-View Representation Learning
Yu Geng, Zongbo Han, Changqing Zhang +1
Learning from different data views by exploring the underlying complementary information among them can endow the representation with stronger expressive ability. However, high-dim…
Trustworthy Multimodal Regression with Mixture of Normal-inverse Gamma Distributions
Huan Ma, Zongbo Han, Changqing Zhang +3
Multimodal regression is a fundamental task, which integrates the information from different sources to improve the performance of follow-up applications. However, existing methods…
Trustworthy Long-Tailed Classification
Bolian Li, Zongbo Han, Haining Li +2
Classification on long-tailed distributed data is a challenging problem, which suffers from serious class-imbalance and accordingly unpromising performance especially on tail class…
Trusted Multi-View Classification
Zongbo Han, Changqing Zhang, Huazhu Fu +1
Multi-view classification (MVC) generally focuses on improving classification accuracy by using information from different views, typically integrating them into a unified comprehe…
Deep Partial Multi-View Learning
Changqing Zhang, Yajie Cui, Zongbo Han +3
Although multi-view learning has made signifificant progress over the past few decades, it is still challenging due to the diffificulty in modeling complex correlations among diffe…
SPL-MLL: Selecting Predictable Landmarks for Multi-Label Learning
Junbing Li, Changqing Zhang, Pengfei Zhu +3
Although significant progress achieved, multi-label classification is still challenging due to the complexity of correlations among different labels. Furthermore, modeling the rela…
M2Net: Multi-modal Multi-channel Network for Overall Survival Time Prediction of Brain Tumor Patients
Tao Zhou, Huazhu Fu, Yu Zhang +4
Early and accurate prediction of overall survival (OS) time can help to obtain better treatment planning for brain tumor patients. Although many OS time prediction methods have bee…
Diagnosis of Coronavirus Disease 2019 (COVID-19) with Structured Latent Multi-View Representation Learning
Hengyuan Kang, Liming Xia, Fuhua Yan +8
Recently, the outbreak of Coronavirus Disease 2019 (COVID-19) has spread rapidly across the world. Due to the large number of affected patients and heavy labor for doctors, compute…
Multi-view Deep Subspace Clustering Networks
Pengfei Zhu, Xinjie Yao, Yu Wang +3
Multi-view subspace clustering aims to discover the inherent structure of data by fusing multiple views of complementary information. Most existing methods first extract multiple t…
Unsupervised Degradation Learning for Single Image Super-Resolution
Tianyu Zhao, Wenqi Ren, Changqing Zhang +2
Deep Convolution Neural Networks (CNN) have achieved significant performance on single image super-resolution (SR) recently. However, existing CNN-based methods use artificially sy…
Disc-aware Ensemble Network for Glaucoma Screening from Fundus Image
Huazhu Fu, Jun Cheng, Yanwu Xu +4
Glaucoma is a chronic eye disease that leads to irreversible vision loss. Most of the existing automatic screening methods firstly segment the main structure, and subsequently calc…
Saliency Detection for Stereoscopic Images Based on Depth Confidence Analysis and Multiple Cues Fusion
Runmin Cong, Jianjun Lei, Changqing Zhang +3
Stereoscopic perception is an important part of human visual system that allows the brain to perceive depth. However, depth information has not been well explored in existing salie…