Zobrazeno 1 - 10
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pro vyhledávání: '"Liu, Yutao"'
Autor:
Pan, Wensheng, Gao, Timin, Zhang, Yan, Hu, Runze, Zheng, Xiawu, Zhang, Enwei, Gao, Yuting, Liu, Yutao, Shen, Yunhang, Li, Ke, Zhang, Shengchuan, Cao, Liujuan, Ji, Rongrong
Image Quality Assessment (IQA) models benefit significantly from semantic information, which allows them to treat different types of objects distinctly. Currently, leveraging semantic information to enhance IQA is a crucial research direction. Tradit
Externí odkaz:
http://arxiv.org/abs/2404.14949
Autor:
Li, Xudong, Zheng, Jingyuan, Hu, Runze, Zhang, Yan, Li, Ke, Shen, Yunhang, Zheng, Xiawu, Liu, Yutao, Zhang, ShengChuan, Dai, Pingyang, Ji, Rongrong
Blind Image Quality Assessment (BIQA) aims to evaluate image quality in line with human perception, without reference benchmarks. Currently, deep learning BIQA methods typically depend on using features from high-level tasks for transfer learning. Ho
Externí odkaz:
http://arxiv.org/abs/2401.11949
Concealed object segmentation (COS) is a challenging task that involves localizing and segmenting those concealed objects that are visually blended with their surrounding environments. Despite achieving remarkable success, existing COS segmenters sti
Externí odkaz:
http://arxiv.org/abs/2401.11767
Autor:
Li, Xudong, Gao, Timin, Hu, Runze, Zhang, Yan, Zhang, Shengchuan, Zheng, Xiawu, Zheng, Jingyuan, Shen, Yunhang, Li, Ke, Liu, Yutao, Dai, Pingyang, Ji, Rongrong
The current state-of-the-art No-Reference Image Quality Assessment (NR-IQA) methods typically rely on feature extraction from upstream semantic backbone networks, assuming that all extracted features are relevant. However, we make a key observation t
Externí odkaz:
http://arxiv.org/abs/2312.06158
Autor:
Li, Xudong, Zheng, Jingyuan, Zheng, Xiawu, Hu, Runze, Zhang, Enwei, Gao, Yuting, Shen, Yunhang, Li, Ke, Liu, Yutao, Dai, Pingyang, Zhang, Yan, Ji, Rongrong
Image Quality Assessment (IQA) with reference images have achieved great success by imitating the human vision system, in which the image quality is effectively assessed by comparing the query image with its pristine reference image. However, for the
Externí odkaz:
http://arxiv.org/abs/2312.00591
Underwater image enhancement (UIE) poses challenges due to distinctive properties of the underwater environment, including low contrast, high turbidity, visual blurriness, and color distortion. In recent years, the application of deep learning has qu
Externí odkaz:
http://arxiv.org/abs/2311.00246
The Segment Anything Model (SAM) has revolutionized natural image segmentation, nevertheless, its performance on underwater images is still restricted. This work presents AquaSAM, the first attempt to extend the success of SAM on underwater images wi
Externí odkaz:
http://arxiv.org/abs/2308.04218
Blind Image Quality Assessment (BIQA) is a fundamental task in computer vision, which however remains unresolved due to the complex distortion conditions and diversified image contents. To confront this challenge, we in this paper propose a novel BIQ
Externí odkaz:
http://arxiv.org/abs/2304.04952
Autor:
Gen Lin, Zhijie Wang, Qian Chu, Yi Hu, Dingzhi Huang, Jun Wang, Fan Yang, Wenzhao Zhong, Chengzhi Zhou, Bo Zhu, Xinghao Ai, Baoshan Cao, Yabing Cao, Mingqiu Chen, Xiaohui Chen, Tianqing Chu, Jianchun Duan, Yun Fan, Yong Fang, Shuitu Feng, Weineng Feng, Hui Guo, Chengbo Han, Yong He, Shaodong Hong, Jie Hu, Meijuan Huang, Yan Huang, Da Jiang, Kan Jiang, Richeng Jiang, Bo Jin, Shi Jin, Jisheng Li, Min Li, Ziming Li, Chao Li, Jie Lin, Anwen Liu, Si‐Yang Maggie Liu, Liu Yutao, Zhefeng Liu, Zhe Liu, Zhenhua Liu, Zhentian Liu, Zhigang Liu, Yuping Lu, Tangfeng Lv, Zhiyong Ma, Qian Miao, Min Peng, Xingxiang Pu, Xiu Bao Ren, Jianzhen Shan, Jinlu Shan, Peng Shen, Bo Shen, Meiqi Shi, Yong Song, Zhengbo Song, ChunXia Su, Jianguo Sun, Panwen Tian, Jinliang Wang, Feng Wang, Huijuan Wang, Jialei Wang, Qian Wang, Wenxian Wang, Yan Wang, Lin Wu, Fang Wu, Yang Xia, Congying Xie, Conghua Xie, Tao Xin, Jianping Xiong, Haipeng Xu, Song Xu, Yiquan Xu, Bin Xu, Chunwei Xu, Xiaolong Yan, Zhenzhou Yang, Wenxiu Yao, Yao Yu, Ye Feng, Zongyang Yu, Yongfeng Yu, Dongsheng Yue, Haibo Zhang, HongMei Zhang, Li Zhang, Longfeng Zhang, Qiuyu Zhang, Tongmei Zhang, Bicheng Zhang, Jun Zhao, Mingfang Zhao, Xiaobin Zheng, Qiaofeng Zhong, Jin Zhou, Penghui Zhou, Zhengfei Zhu, Juntao Zou, Zihua Zou
Publikováno v:
Thoracic Cancer, Vol 15, Iss 5, Pp 419-426 (2024)
Abstract Immune checkpoint inhibitor (ICI) rechallenge in non‐small cell lung cancer (NSCLC) is a promising therapeutic strategy. The situation for ICI rechallenge can be divided into three categories: adverse events (AEs); resistance to ICIs, and
Externí odkaz:
https://doaj.org/article/5593cfcf22cf4de189ad661dbe843899
Autor:
Liu, Yutao
We develop a new method in the computation of equivariant homotopy, which is based on the splitting of cofiber sequences associated to universal spaces in the category of equivariant spectra. In particular, we use this method to compute the homotopy
Externí odkaz:
http://arxiv.org/abs/2203.14361