no code implementations • 23 Oct 2023 • Xinliang Zhang, Mojtaba Vaezi
The proposed structure significantly enhances the performance of the ZIC both for the perfect and imperfect CSI.
no code implementations • 21 Sep 2023 • Shuang Zeng, Lei Zhu, Xinliang Zhang, Zifeng Tian, Qian Chen, Lujia Jin, Jiayi Wang, Yanye Lu
In this work, we propose a novel asymmetric contrastive learning framework named JCL for medical image segmentation with self-supervised pre-training.
1 code implementation • ICCV 2023 • Chengliang Zhong, Yuhang Zheng, Yupeng Zheng, Hao Zhao, Li Yi, Xiaodong Mu, Ling Wang, Pengfei Li, Guyue Zhou, Chao Yang, Xinliang Zhang, Jian Zhao
To address this issue, the Transporter method was introduced for 2D data, which reconstructs the target frame from the source frame to incorporate both spatial and temporal information.
no code implementations • 9 Aug 2023 • Lei Zhu, Hangzhou He, Xinliang Zhang, Qian Chen, Shuang Zeng, Qiushi Ren, Yanye Lu
Existing methods adopt an online-trained classification branch to provide pseudo annotations for supervising the segmentation branch.
no code implementations • 17 Feb 2022 • Yuhan Yao, Yuhe Zhao, Yanxian Wei, Feng Zhou, Daigao Chen, Yuguang Zhang, Xi Xiao, Ming Li, Jianji Dong, Shaohua Yu, Xinliang Zhang
We demonstrate a fully-integrated multipurpose microwave frequency identification system on silicon-on-insulator platform.
no code implementations • 3 Nov 2021 • Xinliang Zhang, Mojtaba Vaezi, Timothy J. O'Shea
SVDembedded DAE largely outperforms theoretic linear precoding in terms of BER.
no code implementations • 6 Jul 2020 • Xinliang Zhang, Mojtaba Vaezi
Numerical results demonstrate that, compared to the conventional solutions, the proposed DNN-based precoder reduces on-the-fly computational complexity more than an order of magnitude while reaching near-optimal performance (99. 45\% of the averaged optimal solutions).
no code implementations • 17 Sep 2019 • Xinliang Zhang, Mojtaba Vaezi
A novel precoding method based on supervised deep neural networks is introduced for the multiple-input multiple-output Gaussian wiretap channel.