Zobrazeno 1 - 10
of 244
pro vyhledávání: '"Chen, Qingliang"'
Autor:
Xu, Zhiyu, Chen, Qingliang
Driven by large data trained segmentation models, such as SAM , research in one-shot segmentation has experienced significant advancements. Recent contributions like PerSAM and MATCHER , presented at ICLR 2024, utilize a similar approach by leveragin
Externí odkaz:
http://arxiv.org/abs/2405.11476
Autor:
Xu, Zhiyu, Chen, Qingliang
Glass-like objects can be seen everywhere in our daily life which are very hard for existing methods to segment them. The properties of transparencies pose great challenges of detecting them from the chaotic background and the vague separation bounda
Externí odkaz:
http://arxiv.org/abs/2402.08571
Autor:
Cheng, Shuangqin, Chen, Qingliang, Zhang, Qiyi, Li, Ming, Alike, Yamuhanmode, Su, Kaile, Wen, Pengcheng
Computed Tomography (CT) is a medical imaging modality that can generate more informative 3D images than 2D X-rays. However, this advantage comes at the expense of more radiation exposure, higher costs, and longer acquisition time. Hence, the reconst
Externí odkaz:
http://arxiv.org/abs/2309.04960
Prompt-based learning has been proved to be an effective way in pre-trained language models (PLMs), especially in low-resource scenarios like few-shot settings. However, the trustworthiness of PLMs is of paramount significance and potential vulnerabi
Externí odkaz:
http://arxiv.org/abs/2306.05659
Autor:
Li Jinghui, Yang Yin, Muhetaer Xiaokaitijiang, Tang Yipeng, Wang Lianqun, Bai Yunpeng, Zhang Zhejun, Jiang Nan, Wang Qiang, Chen Qingliang, Xu Dong, Yang Dongyan, Guo Zhigang, Zhao Feng
Publikováno v:
Journal of International Medical Research, Vol 52 (2024)
Objective To compare the clinical effects of coronary artery bypass grafting (CABG) between the left anterior small thoracotomy (LAST) and lower-end sternal splitting (LESS) approaches for coronary artery disease. Methods In total, 110 patients who u
Externí odkaz:
https://doaj.org/article/1c1c2c42060e4476b7897723682734cd
Autor:
Chen, Qingliang, Li, Yu, Zhang, Yuansen, Wang, Qiuyue, Li, Yongting, Zheng, Wen-Hua, Guo, Xuefeng
Publikováno v:
In Applied Catalysis O: Open September 2024 194
Publikováno v:
In Heliyon 15 August 2024 10(15)
Fine-grained Visual Classification (FGVC) aims to identify objects from subcategories. It is a very challenging task because of the subtle inter-class differences. Existing research applies large-scale convolutional neural networks or visual transfor
Externí odkaz:
http://arxiv.org/abs/2112.04223
Graph-based Aspect-based Sentiment Classification (ABSC) approaches have yielded state-of-the-art results, expecially when equipped with contextual word embedding from pre-training language models (PLMs). However, they ignore sequential features of t
Externí odkaz:
http://arxiv.org/abs/2110.00171