1 code implementation • 23 Oct 2023 • Yujie Feng, Zexin Lu, Bo Liu, LiMing Zhan, Xiao-Ming Wu
In this study, we conduct an initial examination of ChatGPT's capabilities in DST.
1 code implementation • 20 Aug 2023 • Bo Liu, LiMing Zhan, Zexin Lu, Yujie Feng, Lei Xue, Xiao-Ming Wu
Out-of-distribution (OOD) detection plays a vital role in enhancing the reliability of machine learning (ML) models.
Out-of-Distribution Detection Out of Distribution (OOD) Detection
1 code implementation • 8 Jun 2022 • Ziyuan Yang, Wenjun Xia, Zexin Lu, Yingyu Chen, Xiaoxiao Li, Yi Zhang
The basic assumption of HyperFed is that the optimization problem for each institution can be divided into two parts: the local data adaption problem and the global CT imaging problem, which are implemented by an institution-specific hypernetwork and a global-sharing imaging network, respectively.
1 code implementation • ACL 2021 • Zexin Lu, Keyang Ding, Yuji Zhang, Jing Li, Baolin Peng, Lemao Liu
This paper presents a novel task to generate poll questions for social media posts.
Ranked #3 on Answer Generation on WeiboPolls
no code implementations • 14 May 2021 • Zhiwen Wang, Wenjun Xia, Zexin Lu, Yongqiang Huang, Yan Liu, Hu Chen, Jiliu Zhou, Yi Zhang
Magnetic resonance imaging (MRI) acquisition, reconstruction, and segmentation are usually processed independently in the conventional practice of MRI workflow.
no code implementations • 3 Apr 2021 • Tao Wang, Wenjun Xia, Zexin Lu, Huaiqiang Sun, Yan Liu, Hu Chen, Jiliu Zhou, Yi Zhang
Since the dual-domain MAR methods can leverage the hybrid information from both sinogram and image domains, they have significantly improved the performance compared to single-domain methods.
no code implementations • 24 Mar 2021 • Zexin Lu, Wenjun Xia, Yongqiang Huang, Hongming Shan, Hu Chen, Jiliu Zhou, Yi Zhang
Recent advance on neural network architecture search (NAS) has proved that the network architecture has a dramatic effect on the model performance, which indicates that current network architectures for LDCT may be sub-optimal.
no code implementations • 27 Oct 2020 • Wenjun Xia, Zexin Lu, Yongqiang Huang, Yan Liu, Hu Chen, Jiliu Zhou, Yi Zhang
Current mainstream of CT reconstruction methods based on deep learning usually needs to fix the scanning geometry and dose level, which will significantly aggravate the training cost and need more training data for clinical application.