Zobrazeno 1 - 10
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pro vyhledávání: '"YU Wenwen"'
Publikováno v:
Pifu-xingbing zhenliaoxue zazhi, Vol 31, Iss 9, Pp 652-656 (2024)
Systemic sclerosis (SSc), an autoimmune disorder, is mainly manifested by the skin thickening and hardening, with involvements of the internal organs and blood vessels. Currently, no definitive and effective treatments are available for SSc, and the
Externí odkaz:
https://doaj.org/article/059afdc63f33449fb6fe2b7c6dd3c6fd
Autor:
XIE Xiaomin (谢小敏), ZHANG Yanmei (张焱梅), PAN Tiantian (潘甜甜), CAO Jing (曹静), YU Wenwen (於雯雯), WU Jingjing (吴静静), ZHAO Huan (赵焕)
Publikováno v:
中西医结合护理, Vol 9, Iss 4, Pp 156-161 (2023)
Objective To investigate the effect of Shang-tune music on the relief of negative emotions in patients with chronic obstructive pulmonary disease (COPD), and to analyze potential factors influencing the efficacy of the intervention. Methods A prospec
Externí odkaz:
https://doaj.org/article/aae1b74e4af047459da253efeaec99c0
Autor:
Wan, Jianqiang, Song, Sibo, Yu, Wenwen, Liu, Yuliang, Cheng, Wenqing, Huang, Fei, Bai, Xiang, Yao, Cong, Yang, Zhibo
Recently, visually-situated text parsing (VsTP) has experienced notable advancements, driven by the increasing demand for automated document understanding and the emergence of Generative Large Language Models (LLMs) capable of processing document-bas
Externí odkaz:
http://arxiv.org/abs/2403.19128
Autor:
Cao, Guangming, Yu, Xuehui, Yu, Wenwen, Han, Xumeng, Yang, Xue, Li, Guorong, Jiao, Jianbin, Han, Zhenjun
Single-point annotation in oriented object detection of remote sensing scenarios is gaining increasing attention due to its cost-effectiveness. However, due to the granularity ambiguity of points, there is a significant performance gap between previo
Externí odkaz:
http://arxiv.org/abs/2311.13128
We exploit the potential of the large-scale Contrastive Language-Image Pretraining (CLIP) model to enhance scene text detection and spotting tasks, transforming it into a robust backbone, FastTCM-CR50. This backbone utilizes visual prompt learning an
Externí odkaz:
http://arxiv.org/abs/2308.10408
Autor:
Yu, Wenwen, Liu, Mingyu, Yang, Biao, Zhang, Enming, Jiang, Deqiang, Sun, Xing, Liu, Yuliang, Bai, Xiang
Text recognition in the wild is a long-standing problem in computer vision. Driven by end-to-end deep learning, recent studies suggest vision and language processing are effective for scene text recognition. Yet, solving edit errors such as add, dele
Externí odkaz:
http://arxiv.org/abs/2306.03482
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:
Liu, Yuliang, Li, Zhang, Huang, Mingxin, Yang, Biao, Yu, Wenwen, Li, Chunyuan, Yin, Xucheng, Liu, Cheng-lin, Jin, Lianwen, Bai, Xiang
Large models have recently played a dominant role in natural language processing and multimodal vision-language learning. However, their effectiveness in text-related visual tasks remains relatively unexplored. In this paper, we conducted a comprehen
Externí odkaz:
http://arxiv.org/abs/2305.07895
Autor:
Yu, Wenwen, Liu, Mingyu, Chen, Mingrui, Lu, Ning, Wen, Yinlong, Liu, Yuliang, Karatzas, Dimosthenis, Bai, Xiang
Reading seal title text is a challenging task due to the variable shapes of seals, curved text, background noise, and overlapped text. However, this important element is commonly found in official and financial scenarios, and has not received the att
Externí odkaz:
http://arxiv.org/abs/2304.11966
The recent large-scale Contrastive Language-Image Pretraining (CLIP) model has shown great potential in various downstream tasks via leveraging the pretrained vision and language knowledge. Scene text, which contains rich textual and visual informati
Externí odkaz:
http://arxiv.org/abs/2302.14338