no code implementations • 1 Apr 2024 • Jun Lyu, Chen Qin, Shuo Wang, Fanwen Wang, Yan Li, Zi Wang, Kunyuan Guo, Cheng Ouyang, Michael Tänzer, Meng Liu, Longyu Sun, Mengting Sun, Qin Li, Zhang Shi, Sha Hua, Hao Li, Zhensen Chen, Zhenlin Zhang, Bingyu Xin, Dimitris N. Metaxas, George Yiasemis, Jonas Teuwen, Liping Zhang, Weitian Chen, Yidong Zhao, Qian Tao, Yanwei Pang, Xiaohan Liu, Artem Razumov, Dmitry V. Dylov, Quan Dou, Kang Yan, Yuyang Xue, Yuning Du, Julia Dietlmeier, Carles Garcia-Cabrera, Ziad Al-Haj Hemidi, Nora Vogt, Ziqiang Xu, Yajing Zhang, Ying-Hua Chu, Weibo Chen, Wenjia Bai, Xiahai Zhuang, Jing Qin, Lianmin Wu, Guang Yang, Xiaobo Qu, He Wang, Chengyan Wang
To address this issue, we organized the Cardiac MRI Reconstruction Challenge (CMRxRecon) in 2023, in collaboration with the 26th International Conference on MICCAI.
no code implementations • 2 Feb 2024 • Xiaohan Liu, ChiJui Chen, YanLun Huang, LingChi Yang, Elham E Khoda, Yihui Chen, Scott Hauck, Shih-Chieh Hsu, Bo-Cheng Lai
Our implementation shows an inference latency of 41. 97 $\mu$s for processing the data in a single trial on a Xilinx U55C.
no code implementations • 16 Jan 2024 • Gengyue Han, Xiaohan Liu, Xianyue Peng, Hao Wang, Yu Han
This study introduces CycLight, a novel cycle-level deep reinforcement learning (RL) approach for network-level adaptive traffic signal control (NATSC) systems.
no code implementations • 5 Jun 2023 • Xiaohan Liu, Yanwei Pang, Xuebin Sun, Yiming Liu, Yonghong Hou, ZhenChang Wang, Xuelong Li
To address this problem, we propose the following: (1) a novel convolutional operator called Faster Fourier Convolution (FasterFC) to replace the two consecutive convolution operations typically used in convolutional neural networks (e. g., U-Net, ResNet).
no code implementations • 11 Mar 2022 • Xiaohan Liu, Yanwei Pang, Ruiqi Jin, Yu Liu, ZhenChang Wang
Purpose: To introduce a dual-domain reconstruction network with V-Net and K-Net for accurate MR image reconstruction from undersampled k-space data.
no code implementations • 10 Feb 2014 • Xintong Yu, Xiaohan Liu, Yisong Chen
We propose a foreground segmentation algorithm that does foreground extraction under different scales and refines the result by matting.