Zobrazeno 1 - 10
of 57
pro vyhledávání: '"Du, Yuning"'
Despite the high diagnostic accuracy of Magnetic Resonance Imaging (MRI), using MRI as a Point-of-Care (POC) disease identification tool poses significant accessibility challenges due to the use of high magnetic field strength and lengthy acquisition
Externí odkaz:
http://arxiv.org/abs/2406.16754
Autor:
Lyu, Jun, Qin, Chen, Wang, Shuo, Wang, Fanwen, Li, Yan, Wang, Zi, Guo, Kunyuan, Ouyang, Cheng, Tänzer, Michael, Liu, Meng, Sun, Longyu, Sun, Mengting, Li, Qin, Shi, Zhang, Hua, Sha, Li, Hao, Chen, Zhensen, Zhang, Zhenlin, Xin, Bingyu, Metaxas, Dimitris N., Yiasemis, George, Teuwen, Jonas, Zhang, Liping, Chen, Weitian, Zhao, Yidong, Tao, Qian, Pang, Yanwei, Liu, Xiaohan, Razumov, Artem, Dylov, Dmitry V., Dou, Quan, Yan, Kang, Xue, Yuyang, Du, Yuning, Dietlmeier, Julia, Garcia-Cabrera, Carles, Hemidi, Ziad Al-Haj, Vogt, Nora, Xu, Ziqiang, Zhang, Yajing, Chu, Ying-Hua, Chen, Weibo, Bai, Wenjia, Zhuang, Xiahai, Qin, Jing, Wu, Lianmin, Yang, Guang, Qu, Xiaobo, Wang, He, Wang, Chengyan
Cardiac MRI, crucial for evaluating heart structure and function, faces limitations like slow imaging and motion artifacts. Undersampling reconstruction, especially data-driven algorithms, has emerged as a promising solution to accelerate scans and e
Externí odkaz:
http://arxiv.org/abs/2404.01082
Deep learning (DL) reconstruction particularly of MRI has led to improvements in image fidelity and reduction of acquisition time. In neuroimaging, DL methods can reconstruct high-quality images from undersampled data. However, it is essential to con
Externí odkaz:
http://arxiv.org/abs/2309.14392
Autor:
Xue, Yuyang, Du, Yuning, Carloni, Gianluca, Pachetti, Eva, Jordan, Connor, Tsaftaris, Sotirios A.
Cine Magnetic Resonance Imaging (MRI) allows for understanding of the heart's function and condition in a non-invasive manner. Undersampling of the $k$-space is employed to reduce the scan duration, thus increasing patient comfort and reducing the ri
Externí odkaz:
http://arxiv.org/abs/2309.13385
Autor:
Du, Yongkun, Chen, Zhineng, Jia, Caiyan, Yin, Xiaoting, Li, Chenxia, Du, Yuning, Jiang, Yu-Gang
Scene text recognition (STR) methods have struggled to attain high accuracy and fast inference speed. Autoregressive (AR)-based models implement the recognition in a character-by-character manner, showing superiority in accuracy but with slow inferen
Externí odkaz:
http://arxiv.org/abs/2307.12270
Autor:
Su, Yuchen, Chen, Zhineng, Shao, Zhiwen, Du, Yuning, Ji, Zhilong, Bai, Jinfeng, Zhou, Yong, Jiang, Yu-Gang
Recently, regression-based methods, which predict parameterized text shapes for text localization, have gained popularity in scene text detection. However, the existing parameterized text shape methods still have limitations in modeling arbitrary-sha
Externí odkaz:
http://arxiv.org/abs/2306.15142
Autor:
Yu, Wenwen, Zhang, Chengquan, Cao, Haoyu, Hua, Wei, Li, Bohan, Chen, Huang, Liu, Mingyu, Chen, Mingrui, Kuang, Jianfeng, Cheng, Mengjun, Du, Yuning, Feng, Shikun, Hu, Xiaoguang, Lyu, Pengyuan, Yao, Kun, Yu, Yuechen, Liu, Yuliang, Che, Wanxiang, Ding, Errui, Liu, Cheng-Lin, Luo, Jiebo, Yan, Shuicheng, Zhang, Min, Karatzas, Dimosthenis, Sun, Xing, Wang, Jingdong, Bai, Xiang
Structured text extraction is one of the most valuable and challenging application directions in the field of Document AI. However, the scenarios of past benchmarks are limited, and the corresponding evaluation protocols usually focus on the submodul
Externí odkaz:
http://arxiv.org/abs/2306.03287
Autor:
Li, Chenxia, Guo, Ruoyu, Zhou, Jun, An, Mengtao, Du, Yuning, Zhu, Lingfeng, Liu, Yi, Hu, Xiaoguang, Yu, Dianhai
A large amount of document data exists in unstructured form such as raw images without any text information. Designing a practical document image analysis system is a meaningful but challenging task. In previous work, we proposed an intelligent docum
Externí odkaz:
http://arxiv.org/abs/2210.05391
Autor:
Li, Chenxia, Liu, Weiwei, Guo, Ruoyu, Yin, Xiaoting, Jiang, Kaitao, Du, Yongkun, Du, Yuning, Zhu, Lingfeng, Lai, Baohua, Hu, Xiaoguang, Yu, Dianhai, Ma, Yanjun
Optical character recognition (OCR) technology has been widely used in various scenes, as shown in Figure 1. Designing a practical OCR system is still a meaningful but challenging task. In previous work, considering the efficiency and accuracy, we pr
Externí odkaz:
http://arxiv.org/abs/2206.03001
Autor:
Du, Yongkun, Chen, Zhineng, Jia, Caiyan, Yin, Xiaoting, Zheng, Tianlun, Li, Chenxia, Du, Yuning, Jiang, Yu-Gang
Dominant scene text recognition models commonly contain two building blocks, a visual model for feature extraction and a sequence model for text transcription. This hybrid architecture, although accurate, is complex and less efficient. In this study,
Externí odkaz:
http://arxiv.org/abs/2205.00159