Multi-frequency Electrical Impedance Tomography Reconstruction with Multi-Branch Attention Image Prior

no code implementations • 17 Sep 2024 • Hao Fang, Zhe Liu, Yi Feng, Zhen Qiu, Pierre Bagnaninchi, Yunjie Yang

Moreover, the dependency on training data in supervised MMV methods can introduce erroneous conductivity contrasts across frequencies, posing significant concerns in biomedical applications.

Prototype-Driven Multi-Feature Generation for Visible-Infrared Person Re-identification

1 code implementation • 9 Sep 2024 • Jiarui Li, Zhen Qiu, Yilin Yang, Yuqi Li, Zeyu Dong, Chuanguang Yang

The primary challenges in visible-infrared person re-identification arise from the differences between visible (vis) and infrared (ir) images, including inter-modal and intra-modal variations.

Diversity Person Re-Identification

Imbalance-Agnostic Source-Free Domain Adaptation via Avatar Prototype Alignment

no code implementations • 22 May 2023 • Hongbin Lin, Mingkui Tan, Yifan Zhang, Zhen Qiu, Shuaicheng Niu, Dong Liu, Qing Du, Yanxia Liu

To address this issue, we study a more practical SF-UDA task, termed imbalance-agnostic SF-UDA, where the class distributions of both the unseen source domain and unlabeled target domain are unknown and could be arbitrarily skewed.

Pseudo Label Source-Free Domain Adaptation +1

Multi-Scale Multi-Target Domain Adaptation for Angle Closure Classification

no code implementations • 25 Aug 2022 • Zhen Qiu, Yifan Zhang, Fei Li, Xiulan Zhang, Yanwu Xu, Mingkui Tan

Based on these domain-invariant features at different scales, the deep model trained on the source domain is able to classify angle closure on multiple target domains even without any annotations in these domains.

Domain Adaptation Multi-target Domain Adaptation

Prototype-Guided Continual Adaptation for Class-Incremental Unsupervised Domain Adaptation

1 code implementation • 22 Jul 2022 • Hongbin Lin, Yifan Zhang, Zhen Qiu, Shuaicheng Niu, Chuang Gan, Yanxia Liu, Mingkui Tan

2) Prototype-based alignment and replay: based on the identified label prototypes, we align both domains and enforce the model to retain previous knowledge.

Unsupervised Domain Adaptation

Source-free Domain Adaptation via Avatar Prototype Generation and Adaptation

1 code implementation • 18 Jun 2021 • Zhen Qiu, Yifan Zhang, Hongbin Lin, Shuaicheng Niu, Yanxia Liu, Qing Du, Mingkui Tan

(2) prototype adaptation: based on the generated source prototypes and target pseudo labels, we develop a new robust contrastive prototype adaptation strategy to align each pseudo-labeled target data to the corresponding source prototypes.

Contrastive Learning Source-Free Domain Adaptation +1

COVID-DA: Deep Domain Adaptation from Typical Pneumonia to COVID-19

1 code implementation • 30 Apr 2020 • Yifan Zhang, Shuaicheng Niu, Zhen Qiu, Ying WEI, Peilin Zhao, Jianhua Yao, Junzhou Huang, Qingyao Wu, Mingkui Tan

There are two main challenges: 1) the discrepancy of data distributions between domains; 2) the task difference between the diagnosis of typical pneumonia and COVID-19.

COVID-19 Diagnosis Domain Adaptation