Cost sensitive adaptive random subspace ensemble for computer-aided nodule detection. - Peng Cao 001; Dazhe Zhao; Osmar R. Zaïane (CBMS, 2013)

Measure oriented cost-sensitive SVM for 3D nodule detection. - Peng Cao 001; Dazhe Zhao; Osmar R. Zaïane (EMBC, 2013)

Measure optimized cost-sensitive neural network ensemble for multiclass imbalance data learning. - Peng Cao 001; Dazhe Zhao; Osmar R. Zaïane (HIS, 2013)

A novel cost sensitive neural network ensemble for multiclass imbalance data learning. - Peng Cao 001; Bo Li 041; Dazhe Zhao; Osmar R. Zaïane (IJCNN, 2013)

Measure optimized wrapper framework for multi-class imbalanced data learning: An empirical study. - Peng Cao 001; Dazhe Zhao; Osmar R. Zaïane (IJCNN, 2013)

An Optimized Cost-Sensitive SVM for Imbalanced Data Learning. - Peng Cao 001; Dazhe Zhao; Osmar R. Zaïane (PAKDD (2), 2013)

A PSO-Based Cost-Sensitive Neural Network for Imbalanced Data Classification. - Peng Cao 001; Dazhe Zhao; Osmar R. Zaïane (PAKDD Workshops, 2013)

On the application of multi-class classification in physical therapy recommendation. - Jing Zhang; Peng Cao 001; Douglas P. Gross; Osmar R. Zaïane (Health Inf. Sci. Syst., 2013)

Ensemble-based hybrid probabilistic sampling for imbalanced data learning in lung nodule CAD. - Peng Cao 001; Jinzhu Yang; Wei Li 117; Dazhe Zhao; Osmar R. Zaïane (Comput. Medical Imaging Graph., 2014)

Hybrid probabilistic sampling with random subspace for imbalanced data learning. - Peng Cao 001; Dazhe Zhao; Osmar R. Zaïane (Intell. Data Anal., 2014)

Cost Sensitive Ranking Support Vector Machine for Multi-label Data Learning. - Peng Cao 001; Xiaoli Liu 001; Dazhe Zhao; Osmar R. Zaïane (HIS, 2016)

Sparse Learning and Hybrid Probabilistic Oversampling for Alzheimer's Disease Diagnosis. - Peng Cao 001; Xiaoli Liu 001; Dazhe Zhao; Osmar R. Zaïane (HIS, 2016)

Pulmonary Nodule Classification with Deep Convolutional Neural Networks on Computed Tomography Images. - Wei Li 117; Peng Cao 001; Dazhe Zhao; Junbo Wang (Comput. Math. Methods Medicine, 2016)

Group Guided Sparse Group Lasso Multi-task Learning for Cognitive Performance Prediction of Alzheimer's Disease. - Xiaoli Liu 001; Peng Cao 001; Jinzhu Yang; Dazhe Zhao; Osmar R. Zaïane (BI, 2017)

Sparse Multi-kernel Based Multi-task Learning for Joint Prediction of Clinical Scores and Biomarker Identification in Alzheimer's Disease. - Peng Cao 001; Xiaoli Liu 001; Jinzhu Yang; Dazhe Zhao; Osmar R. Zaïane (MICCAI (3), 2017)

Nonlinearity-aware based dimensionality reduction and over-sampling for AD/MCI classification from MRI measures. - Peng Cao 001; Xiaoli Liu 001; Jinzhu Yang; Dazhe Zhao; Min Huang 001; Jian Zhang; Osmar R. Zaïane (Comput. Biol. Medicine, 2017)

Ensemble based adaptive over-sampling method for imbalanced data learning in computer aided detection of microaneurysm. - Fulong Ren; Peng Cao 001; Wei Li 117; Dazhe Zhao; Osmar R. Zaïane (Comput. Medical Imaging Graph., 2017)

A ℓ2, 1 norm regularized multi-kernel learning for false positive reduction in Lung nodule CAD. - Peng Cao 001; Xiaoli Liu 001; Jian Zhang; Wei Li 117; Dazhe Zhao; Min Huang 001; Osmar R. Zaïane (Comput. Methods Programs Biomed., 2017)

ℓ2, 1 norm regularized multi-kernel based joint nonlinear feature selection and over-sampling for imbalanced data classification. - Peng Cao 001; Xiaoli Liu 001; Jian Zhang; Dazhe Zhao; Min Huang 001; Osmar R. Zaïane (Neurocomputing, 2017)

A multi-kernel based framework for heterogeneous feature selection and over-sampling for computer-aided detection of pulmonary nodules. - Peng Cao 001; Xiaoli Liu 001; Jinzhu Yang; Dazhe Zhao; Wei Li 117; Min Huang 001; Osmar R. Zaïane (Pattern Recognit., 2017)

Sparse shared structure based multi-task learning for MRI based cognitive performance prediction of Alzheimer's disease. - Peng Cao 001; Xuanfeng Shan; Dazhe Zhao; Min Huang 001; Osmar R. Zaïane (Pattern Recognit., 2017)

Efficient multi-kernel multi-instance learning using weakly supervised and imbalanced data for diabetic retinopathy diagnosis. - Peng Cao 001; Fulong Ren; Chao Wan; Jinzhu Yang; Osmar R. Zaïane (Comput. Medical Imaging Graph., 2018)

Modeling Alzheimer's disease cognitive scores using multi-task sparse group lasso. - Xiaoli Liu 001; André R. Gonçalves 001; Peng Cao 001; Dazhe Zhao; Arindam Banerjee 001 (Comput. Medical Imaging Graph., 2018)

Linearized and Kernelized Sparse Multitask Learning for Predicting Cognitive Outcomes in Alzheimer's Disease. - Xiaoli Liu 001; Peng Cao 001; Jinzhu Yang; Dazhe Zhao (Comput. Math. Methods Medicine, 2018)

Generalized fused group lasso regularized multi-task feature learning for predicting cognitive outcomes in Alzheimers disease. - Peng Cao 001; Xiaoli Liu 001; Hezi Liu; Jinzhu Yang; Dazhe Zhao; Min Huang 001; Osmar R. Zaïane (Comput. Methods Programs Biomed., 2018)

ℓ2, 1-ℓ1 regularized nonlinear multi-task representation learning based cognitive performance prediction of Alzheimer's disease. - Peng Cao 001; Xiaoli Liu 001; Jinzhu Yang; Dazhe Zhao; Min Huang 001; Osmar R. Zaïane (Pattern Recognit., 2018)

Modeling Alzheimer's Disease Progression with Fused Laplacian Sparse Group Lasso. - Xiaoli Liu 001; Peng Cao 001; André R. Gonçalves 001; Dazhe Zhao; Arindam Banerjee 001 (ACM Trans. Knowl. Discov. Data, 2018)

An ensemble framework with $l_{21}$-norm regularized hypergraph laplacian multi-label learning for clinical data prediction. - Peng Cao 001; Shanshan Tang; Min Huang 001; Jinzhu Yang; Dazhe Zhao; Amine Trabelsi; Osmar R. Zaïane (BIBM, 2019)

Feature-aware Multi-task feature learning for Predicting Cognitive Outcomes in Alzheimer's disease. - Peng Cao 001; Shanshan Tang; Min Huang 001; Jinzhu Yang; Dazhe Zhao; Amine Trabelsi; Osmar R. Zaïane (BIBM, 2019)

A 3D Multi-scale Virtual Adversarial Network for False Positive Reduction in Pulmonary Nodule Detection. - Yunheng Wu; Yuxuan Pang; Peng Cao 001 (ICIAI, 2019)

Fused Group Lasso Regularized Multi-Task Feature Learning and Its Application to the Cognitive Performance Prediction of Alzheimer's Disease. - Xiaoli Liu 001; Peng Cao 001; Jianzhong Wang; Jun Kong 004; Dazhe Zhao (Neuroinformatics, 2019)

A robust fuzzy clustering algorithm using spatial information combined with local membership filtering for brain MR images. - Lanting Li; Peng Cao 001; Jinzhu Yang; Dazhe Zhao; Osmar R. Zaïane (BIBM, 2020)

A Domain Adaptation Multi-instance Learning for Diabetic Retinopathy Grading on Retinal Images. - Ruoxian Song; Peng Cao 001; Jinzhu Yang; Dazhe Zhao; Osmar R. Zaïane (BIBM, 2020)

ST-MetaDiagnosis: Meta learning with Spatial Transform for rare skin disease Diagnosis. - Delong Zhang; Mengqun Jin; Peng Cao 001 (BIBM, 2020)

An end-to-end framework for pulmonary nodule detection and false positive reduction from CT Images. - Yafang Chen; Peng Cao 001; Lili Dou; Jinzhu Yang (ISICDM, 2020)

GCN-RNN: An Unified Framework for Modeling the multi-label diagnosis of chest X-ray disease. - Chunyu Jiang; Peng Cao 001; Lili Dou; Jinzhu Yang; Dazhe Zhao (ISICDM, 2020)

AMIL: An attentional multi-instance learning for computer-aided diagnosis of skin diagnosis. - Mengqun Jin; Delong Zhang; Peng Cao 001 (ISICDM, 2020)

SP-MTFL: A self paced multi-task feature learning method for cognitive performance predicting of Alzheimer's disease. - Xiaoli Liu 001; Jiali Li; Peng Cao 001 (ISICDM, 2020)

Modeling Disease Progression with Deep Neural Networks. - Xiaoli Liu 001; Jiali Li; Peng Cao 001 (ISICDM, 2020)

S-GCN: A siamese spectral graph convolutions on brain connectivity networks. - Xiaoli Liu 001; Jiali Li; Peng Cao 001 (ISICDM, 2020)

Deeply Supervised U-Net with Feature Fusion: Automatic COVID-19 Lung Infection Segmentation from CT Images. - Bo Wu; Peng Cao 001; Jinzhu Yang; Qi Yang; Chengxi Yan; Wenxin Wang; Minglei Yang 002; Lili Dou (ISICDM, 2020)

An atlas based level set method for 3D brain structures segmentation. - Junyi Yan; Jinzhu Yang; Wenjun Tan; Peng Cao 001; Lili Dou; Dazhe Zhao (ISICDM, 2020)

An Auto-Encoding Generative Adversarial Networks for Generating Brain Network. - Shan Zhang; Peng Cao 001; Lili Dou; Jinzhu Yang; Dazhe Zhao (ISICDM, 2020)

Hi-GCN: A hierarchical graph convolution network for graph embedding learning of brain network and brain disorders prediction. - Hao Jiang; Peng Cao 001; MingYi Xu; Jinzhu Yang; Osmar R. Zaïane (Comput. Biol. Medicine, 2020)

Joint feature and task aware multi-task feature learning for Alzheimer's disease diagnosis. - Peng Cao 001; Wei Liang; Kai Zhang; Shanshan Tang; Jinzhu Yang (BIBM, 2021)

Temporal Graph Representation Learning for Autism spectrum disorder Brain Networks. - Peng Cao 001; Guangqi Wen; Lanting Li; Xiaoli Liu 001; Jinzhu Yang; Osmar Zaïane (BIBM, 2021)

Rethinking modeling Alzheimer's disease progression from a multi-task learning perspective with deep recurrent neural network. - Wei Liang; Kai Zhang; Peng Cao 001; Xiaoli Liu 001; Jinzhu Yang; Osmar R. Zaïane (Comput. Biol. Medicine, 2021)

MSDS-UNet: A multi-scale deeply supervised 3D U-Net for automatic segmentation of lung tumor in CT. - Jinzhu Yang; Bo Wu; Lanting Li; Peng Cao 001; Osmar R. Zaïane (Comput. Medical Imaging Graph., 2021)

UCTransNet: Rethinking the Skip Connections in U-Net from a Channel-Wise Perspective with Transformer. - Haonan Wang; Peng Cao 001; Jiaqi Wang 013; Osmar R. Zaïane (AAAI, 2022)

DGE-GSIM: A multi-task dual graph embedding learning for graph similarity computation. - Wenhui Tan; Peng Cao 001; Zhiyong Jin; Futao Luo; Guangqi Wen; Weiping Li (ICMLSC, 2022)

Vessel filtering and segmentation of coronary CT angiographic images. - Yan Huang; Jinzhu Yang; Qi Sun; Shuang Ma; Yuliang Yuan; Wenjun Tan; Peng Cao 001; Chaolu Feng (Int. J. Comput. Assist. Radiol. Surg., 2022)

Collaborative learning of weakly-supervised domain adaptation for diabetic retinopathy grading on retinal images. - Peng Cao 001; Qingshan Hou; Ruoxian Song; Haonan Wang; Osmar R. Zaïane (Comput. Biol. Medicine, 2022)

Dual feature correlation guided multi-task learning for Alzheimer's disease prediction. - Shanshan Tang; Peng Cao 001; Min Huang 001; Xiaoli Liu 001; Osmar R. Zaïane (Comput. Biol. Medicine, 2022)

MVS-GCN: A prior brain structure learning-guided multi-view graph convolution network for autism spectrum disorder diagnosis. - Guangqi Wen; Peng Cao 001; Huiwen Bao; Wenju Yang; Tong Zheng 006; Osmar Zaïane (Comput. Biol. Medicine, 2022)

Collaborative learning of graph generation, clustering and classification for brain networks diagnosis. - Wenju Yang; Guangqi Wen; Peng Cao 001; Jinzhu Yang; Osmar R. Zaïane (Comput. Methods Programs Biomed., 2022)

How Live Streaming Changes Shopping Decisions in E-commerce: A Study of Live Streaming Commerce. - Ye Wang 017; Zhicong Lu; Peng Cao 001; Jingyi Chu; Haonan Wang; Roger Wattenhofer (Comput. Support. Cooperative Work., 2022)

Modeling the dynamic brain network representation for autism spectrum disorder diagnosis. - Peng Cao 001; Guangqi Wen; Xiaoli Liu 001; Jinzhu Yang; Osmar R. Zaïane (Medical Biol. Eng. Comput., 2022)

Modeling global and local label correlation with graph convolutional networks for multi-label chest X-ray image classification. - Lanting Li; Peng Cao 001; Jinzhu Yang; Osmar R. Zaïane (Medical Biol. Eng. Comput., 2022)

TE-HI-GCN: An Ensemble of Transfer Hierarchical Graph Convolutional Networks for Disorder Diagnosis. - Lanting Li; Hao Jiang; Guangqi Wen; Peng Cao 001; MingYi Xu; Xiaoli Liu 001; Jinzhu Yang; Osmar R. Zaïane (Neuroinformatics, 2022)

csl-MTFL: Multi-task Feature Learning with Joint Correlation Structure Learning for Alzheimer's Disease Cognitive Performance Prediction. - Wei Liang; Kai Zhang; Peng Cao 001; Xiaoli Liu 001; Jinzhu Yang; Osmar R. Zaïane (ADMA (3), 2023)

Towards Time-Variant-Aware Link Prediction in Dynamic Graph Through Self-supervised Learning. - Guangqi Wen; Peng Cao 001; Zhiyong Jin; Ruoxian Song; Xiaoli Liu 001; Jinzhu Yang; Osmar R. Zaïane (ADMA (4), 2023)

Label Correlation Guided Feature Selection for Multi-label Learning. - Kai Zhang; Wei Liang; Peng Cao 001; Jinzhu Yang; Weiping Li; Osmar R. Zaïane (ADMA (4), 2023)

Co-training with High-Confidence Pseudo Labels for Semi-supervised Medical Image Segmentation. - Zhiqiang Shen; Peng Cao 001; Hua Yang; Xiaoli Liu 001; Jinzhu Yang; Osmar R. Zaïane (IJCAI, 2023)

Lesion-Aware Contrastive Learning for Diabetic Retinopathy Diagnosis. - Shuai Cheng; Qingshan Hou; Peng Cao 001; Jinzhu Yang; Xiaoli Liu 001; Osmar R. Zaïane (MICCAI (7), 2023)

Modeling Alzheimers' Disease Progression from Multi-task and Self-supervised Learning Perspective with Brain Networks. - Wei Liang; Kai Zhang; Peng Cao 001; Pengfei Zhao; Xiaoli Liu 001; Jinzhu Yang; Osmar R. Zaïane (MICCAI (1), 2023)

BrainUSL: Unsupervised Graph Structure Learning for Functional Brain Network Analysis. - Pengshuai Zhang; Guangqi Wen; Peng Cao 001; Jinzhu Yang; Jinyu Zhang; Xizhe Zhang; Xinrong Zhu; Osmar R. Zaïane; Fei Wang 064 (MICCAI (8), 2023)

A Reference-free Self-supervised Domain Adaptation Framework for Low-quality Fundus Image Enhancement. - Qingshan Hou; Peng Cao 001; Jiaqi Wang 013; Xiaoli Liu 001; Jinzhu Yang; Osmar R. Zaïane (ACM Multimedia, 2023)

MS-SSD: multi-scale single shot detector for ship detection in remote sensing images. - Guangqi Wen; Peng Cao 001; Haonan Wang; Hanlin Chen; Xiaoli Liu 001; Jinghui Xu; Osmar R. Zaïane (Appl. Intell., 2023)

Exploiting task relationships for Alzheimer's disease cognitive score prediction via multi-task learning. - Wei Liang; Kai Zhang; Peng Cao 001; Xiaoli Liu 001; Jinzhu Yang; Osmar R. Zaïane (Comput. Biol. Medicine, 2023)

Self-supervised Domain Adaptation for Breaking the Limits of Low-quality Fundus Image Quality Enhancement. - Qingshan Hou; Peng Cao 001; Jiaqi Wang 013; Xiaoli Liu 001; Jinzhu Yang; Osmar R. Zaïane (CoRR, 2023)

Narrowing the semantic gaps in U-Net with learnable skip connections: The case of medical image segmentation. - Haonan Wang; Peng Cao 001; Xiaoli Liu 001; Jinzhu Yang; Osmar Zaïane (CoRR, 2023)

Exploring attention mechanism for graph similarity learning. - Wenhui Tan; Xin Gao; Yiyang Li; Guangqi Wen; Peng Cao 001; Jinzhu Yang; Weiping Li; Osmar R. Zaïane (Knowl. Based Syst., 2023)

Multi-task spatio-temporal augmented net for industry equipment remaining useful life prediction. - Haodong Li; Peng Cao 001; Xingwei Wang 001; Bo Yi; Min Huang 001; Qiuye Sun; Yanfeng Zhang (Adv. Eng. Informatics, 2023)

BrainTGL: A dynamic graph representation learning model for brain network analysis. - Lingwen Liu; Guangqi Wen; Peng Cao 001; Tianshun Hong; Jinzhu Yang; Xizhe Zhang; Osmar R. Zaïane (Comput. Biol. Medicine, 2023)

A unified framework of graph structure learning, graph generation and classification for brain network analysis. - Peng Cao 001; Guangqi Wen; Wenju Yang; Xiaoli Liu 001; Jinzhu Yang; Osmar R. Zaïane (Appl. Intell., 2023)

WS-LungNet: A two-stage weakly-supervised lung cancer detection and diagnosis network. - Zhiqiang Shen; Peng Cao 001; Jinzhu Yang; Osmar R. Zaïane (Comput. Biol. Medicine, 2023)

Image Quality Assessment Guided Collaborative Learning of Image Enhancement and Classification for Diabetic Retinopathy Grading. - Qingshan Hou; Peng Cao 001; Liyu Jia; Leqi Chen; Jinzhu Yang; Osmar R. Zaïane (IEEE J. Biomed. Health Informatics, 2023)

Exploring interpretable graph convolutional networks for autism spectrum disorder diagnosis. - Lanting Li; Guangqi Wen; Peng Cao 001; Xiaoli Liu 001; Osmar R. Zaïane; Jinzhu Yang (Int. J. Comput. Assist. Radiol. Surg., 2023)

EchoEFNet: Multi-task deep learning network for automatic calculation of left ventricular ejection fraction in 2D echocardiography. - Honghe Li; Yonghuai Wang; Mingjun Qu; Peng Cao 001; Chaolu Feng; Jinzhu Yang (Comput. Biol. Medicine, 2023)

Attention guided learnable time-domain filterbanks for speech depression detection. - Wenju Yang; Jiankang Liu; Peng Cao 001; Rongxin Zhu; Yang Wang; Jian K. Liu; Fei Wang 064; Xizhe Zhang (Neural Networks, 2023)

Graph Self-Supervised Learning With Application to Brain Networks Analysis. - Guangqi Wen; Peng Cao 001; Lingwen Liu; Jinzhu Yang; Xizhe Zhang; Fei Wang 064; Osmar R. Zaïane (IEEE J. Biomed. Health Informatics, 2023)

FFANet - Full frequency attention net for automatic diastolic function assessment. - Mingjun Qu; Shitong Wang; Yonghuai Wang; Honghe Li; Lanting Zhao; Peng Cao 001; Jinzhu Yang (Biomed. Signal Process. Control., 2023)

Label correlation guided borderline oversampling for imbalanced multi-label data learning. - Kai Zhang; Zhaoyang Mao; Peng Cao 001; Wei Liang; Jinzhu Yang; Weiping Li; Osmar R. Zaïane (Knowl. Based Syst., 2023)

MCA-UNet: multi-scale cross co-attentional U-Net for automatic medical image segmentation. - Haonan Wang; Peng Cao 001; Jinzhu Yang; Osmar R. Zaïane (Health Inf. Sci. Syst., 2023)

SETTP: Style Extraction and Tunable Inference via Dual-Level Transferable Prompt Learning. - Chunzhen Jin; Yongfeng Huang; Yaqi Wang 004; Peng Cao 001; Osmar Zaïane (ECAI, 2024)

Reusing Transferable Weight Increments for Low-resource Style Generation. - Chunzhen Jin; Eliot Huang; Heng Chang; Yaqi Wang 004; Peng Cao 001; Osmar R. Zaïane (EMNLP, 2024)

Towards Disease-Aware Self-Supervised Dynamic Brain Network Learning For Mental Diagnosis. - Zhiyong Jin; Guangqi Wen; Peng Cao 001; Lingwen Liu; Jinzhu Yang; Xinrong Zhu; Osmar R. Zaïane; Fei Wang 064 (ICASSP, 2024)

Optimizing Learnable Frequency-Domain Filterbanks for Depression Detection via Speech Representation Disentanglement. - Wenju Yang; LeYang Li; Yong Hao; Peng Cao 001; Osmar R. Zaïane (ICONIP (9), 2024)

A Clinical-Oriented Multi-level Contrastive Learning Method for Disease Diagnosis in Low-Quality Medical Images. - Qingshan Hou; Shuai Cheng; Peng Cao 001; Jinzhu Yang; Xiaoli Liu 001; Yih Chung Tham; Osmar R. Zaïane (MICCAI (3), 2024)

Exploring Spatio-temporal Interpretable Dynamic Brain Function with Transformer for Brain Disorder Diagnosis. - Lanting Li; Liuzeng Zhang; Peng Cao 001; Jinzhu Yang; Fei Wang 064; Osmar R. Zaïane (MICCAI (2), 2024)

3D-SAutoMed: Automatic Segment Anything Model for 3D Medical Image Segmentation from Local-Global Perspective. - Junjie Liang; Peng Cao 001; Wenju Yang; Jinzhu Yang; Osmar R. Zaïane (MICCAI (9), 2024)

Self-paced Sample Selection for Barely-Supervised Medical Image Segmentation. - Junming Su; Zhiqiang Shen; Peng Cao 001; Jinzhu Yang; Osmar R. Zaïane (MICCAI (9), 2024)

A Clinical-Oriented Lightweight Network for High-Resolution Medical Image Enhancement. - Yaqi Wang 004; Leqi Chen; Qingshan Hou; Peng Cao 001; Jinzhu Yang; Xiaoli Liu 001; Osmar R. Zaïane (MICCAI (3), 2024)

Progressively Correcting Soft Labels via Teacher Team for Knowledge Distillation in Medical Image Segmentation. - Yaqi Wang 004; Peng Cao 001; Qingshan Hou; Linqi Lan; Jinzhu Yang; Xiaoli Liu 001; Osmar R. Zaïane (MICCAI (9), 2024)

Capturing Temporal Node Evolution via Self-supervised Learning: A New Perspective on Dynamic Graph Learning. - Lingwen Liu; Guangqi Wen; Peng Cao 001; Jinzhu Yang; Weiping Li; Osmar R. Zaïane (WSDM, 2024)

Pre-training enhanced unsupervised contrastive domain adaptation for industrial equipment remaining useful life prediction. - Haodong Li; Peng Cao 001; Xingwei Wang 001; Ying Li 037; Bo Yi; Min Huang 001 (Adv. Eng. Informatics, 2024)

Lesion-aware knowledge distillation for diabetic retinopathy lesion segmentation. - Yaqi Wang 004; Qingshan Hou; Peng Cao 001; Jinzhu Yang; Osmar R. Zaïane (Appl. Intell., 2024)

Label correlation guided discriminative label feature learning for multi-label chest image classification. - Kai Zhang; Wei Liang; Peng Cao 001; Xiaoli Liu 001; Jinzhu Yang; Osmar R. Zaïane (Comput. Methods Programs Biomed., 2024)

Rethinking Barely-Supervised Segmentation from an Unsupervised Domain Adaptation Perspective. - Zhiqiang Shen; Peng Cao 001; Junming Su; Jinzhu Yang; Osmar R. Zaïane (CoRR, 2024)

Adaptive Mix for Semi-Supervised Medical Image Segmentation. - Zhiqiang Shen; Peng Cao 001; Junming Su; Jinzhu Yang; Osmar R. Zaïane (CoRR, 2024)

BrainDAS: Structure-aware domain adaptation network for multi-site brain network analysis. - Ruoxian Song; Peng Cao 001; Guangqi Wen; Pengfei Zhao; Ziheng Huang; Xizhe Zhang; Jinzhu Yang; Osmar R. Zaïane (Medical Image Anal., 2024)

Narrowing the semantic gaps in U-Net with learnable skip connections: The case of medical image segmentation. - Haonan Wang; Peng Cao 001; Jinzhu Yang; Osmar R. Zaïane (Neural Networks, 2024)

Multi-label borderline oversampling technique. - Zeyu Teng; Peng Cao 001; Min Huang 001; Zheming Gao; Xingwei Wang 001 (Pattern Recognit., 2024)

A Collaborative Self-Supervised Domain Adaptation for Low-Quality Medical Image Enhancement. - Qingshan Hou; Yaqi Wang 004; Peng Cao 001; Shuai Cheng; Linqi Lan; Jinzhu Yang; Xiaoli Liu 001; Osmar R. Zaïane (IEEE Trans. Medical Imaging, 2024)

CMR-BENet: A confidence map refinement boundary enhancement network for left ventricular myocardium segmentation. - Qi Yu; Hongxia Ning; Jinzhu Yang; Chen Li 022; Yiqiu Qi; Mingjun Qu; Honghe Li; Song Sun; Peng Cao 001; Chaolu Feng (Comput. Methods Programs Biomed., 2025)

Style Content Decomposition-based Data Augmentation for Domain Generalizable Medical Image Segmentation. - Zhiqiang Shen; Peng Cao 001; Jinzhu Yang; Osmar R. Zaïane; Zhaolin Chen (CoRR, 2025)

FundusGAN: A Hierarchical Feature-Aware Generative Framework for High-Fidelity Fundus Image Generation. - Qingshan Hou; Meng Wang 001; Peng Cao 001; Ke Zou; Xiaoli Liu 001; Huazhu Fu; Osmar R. Zaïane (CoRR, 2025)

Heterogeneous Graph Representation Learning Framework for Resting-State Functional Connectivity Analysis. - Guangqi Wen; Peng Cao 001; Lingwen Liu; Maochun Hao; Siyu Liu; Junjie Zheng; Jinzhu Yang; Osmar R. Zaïane; Fei Wang 064 (IEEE Trans. Medical Imaging, 2025)

CorLabelNet: a comprehensive framework for multi-label chest X-ray image classification with correlation guided discriminant feature learning and oversampling. - Kai Zhang; Wei Liang; Peng Cao 001; Zhaoyang Mao; Jinzhu Yang; Osmar R. Zaïane (Medical Biol. Eng. Comput., 2025)

A Reference-Free Quality Enhancement Framework for Low-Quality Fundus Images. - Qingshan Hou; Yaqi Wang 004; Linqi Lan; Peng Cao 001; Jinzhu Yang; Xiaoli Liu 001; Meng Wang 001; Yih Chung Tham; Osmar R. Zaïane (IEEE Trans. Circuits Syst. Video Technol., 2025)

An Adaptive Federated Domain Generalization Framework for Consumer Electronics Manufacturing Equipment Cross-Factory Fault Detection. - Haodong Li; Xingwei Wang 001; Ying Li 037; Bo Yi; Peng Cao 001; Min Huang 001; Keqin Li 001 (IEEE Trans. Consumer Electron., 2025)

ConStyX: Content Style Augmentation for Generalizable Medical Image Segmentation. - Xi Chen; Zhiqiang Shen; Peng Cao 001; Jinzhu Yang; Osmar R. Zaïane (CoRR, 2025)

Exploring Attention and Self-Supervised Learning Mechanism for Graph Similarity Learning. - Guangqi Wen; Xin Gao; Wenhui Tan; Peng Cao 001; Jinzhu Yang; Weiping Li; Osmar R. Zaïane (IEEE Trans. Neural Networks Learn. Syst., 2025)

SynMatch: Rethinking Consistency in Medical Image Segmentation with Sparse Annotations. - Zhiqiang Shen; Peng Cao 001; Xiaoli Liu 001; Jinzhu Yang; Osmar R. Zaïane (CoRR, 2025)

Adaptive hypergraph and weighted classifier guided spectral learning for multi-label classification. - Zeyu Teng; Min Huang 001; Peng Cao 001; Shanshan Tang; Xingwei Wang 001 (Expert Syst. Appl., 2026)