Adversarial network integrating dual attention and sparse representation for semi-supervised semantic segmentation. - Ge Jin 002; Chuancai Liu; Xu Chen (Inf. Process. Manag., 2021)

An efficient deep neural network framework for COVID-19 lung infection segmentation. - Ge Jin 002; Chuancai Liu; Xu Chen (Inf. Sci., 2022)

Topological GCN for Improving Detection of Hip Landmarks from B-Mode Ultrasound Images. - Tianxiang Huang; Jing Shi; Ge Jin 002; Juncheng Li 003; Jun Wang 024; Jun Du 006; Jun Shi 004 (MICCAI (5), 2024)

Dual-domain MIM based contrastive learning for CAD of developmental dysplasia of the hip with ultrasound images. - Ke Sun; Jing Shi; Ge Jin 002; Juncheng Li 003; Jun Wang 024; Jun Du 006; Jun Shi 004 (Biomed. Signal Process. Control., 2024)

B-mode ultrasound-based CAD by learning using privileged information with dual-level missing modality completion. - Xiao Wang; Xinping Ren; Ge Jin 002; Shihui Ying; Jun Wang 024; Juncheng Li 003; Jun Shi 004 (Comput. Biol. Medicine, 2024)

Cross-to-merge training with class balance strategy for learning with noisy labels. - Qian Zhang 013; Yi Zhu; Ming Yang; Ge Jin 002; Yingwen Zhu; Qiu Chen (Expert Syst. Appl., 2024)

BPT-PLR: A Balanced Partitioning and Training Framework with Pseudo-Label Relaxed Contrastive Loss for Noisy Label Learning. - Qian Zhang 013; Ge Jin 002; Yi Zhu; Hongjian Wei; Qiu Chen (Entropy, 2024)

Multi-resolution based dual-channel UNet with cross clique for medical image dense prediction. - Xueying Zhou; Ge Jin 002; Yang Liu; Juncheng Li 003; Jun Wang 024; Shihui Ying; Yanyan Zheng; Jun Shi 004 (Expert Syst. Appl., 2025)

HGMSurvNet: A two-stage hypergraph learning network for multimodal cancer survival prediction. - Saisai Ding; Linjin Li; Ge Jin 002; Jun Wang 024; Shihui Ying; Jun Shi 004 (Medical Image Anal., 2025)