Zobrazeno 1 - 10
of 1 058
pro vyhledávání: '"Xu, HuiHui"'
Autor:
Wang, Hongqiu, Chen, Yixian, Chen, Wu, Xu, Huihui, Zhao, Haoyu, Sheng, Bin, Fu, Huazhu, Yang, Guang, Zhu, Lei
Ultra-Wide-Field Scanning Laser Ophthalmoscopy (UWF-SLO) images capture high-resolution views of the retina with typically 200 spanning degrees. Accurate segmentation of vessels in UWF-SLO images is essential for detecting and diagnosing fundus disea
Externí odkaz:
http://arxiv.org/abs/2409.04356
Traditional shadow detectors often identify all shadow regions of static images or video sequences. This work presents the Referring Video Shadow Detection (RVSD), which is an innovative task that rejuvenates the classic paradigm by facilitating the
Externí odkaz:
http://arxiv.org/abs/2408.08543
The outdoor vision systems are frequently contaminated by rain streaks and raindrops, which significantly degenerate the performance of visual tasks and multimedia applications. The nature of videos exhibits redundant temporal cues for rain removal w
Externí odkaz:
http://arxiv.org/abs/2407.21773
Regular screening and early discovery of uterine fibroid are crucial for preventing potential malignant transformations and ensuring timely, life-saving interventions. To this end, we collect and annotate the first ultrasound video dataset with 100 v
Externí odkaz:
http://arxiv.org/abs/2407.05703
Autor:
Xu, Huihui, Ashley, Kevin
Publikováno v:
Legal Knowledge and Information Systems 379(2023) 293-298
Traditional evaluation metrics like ROUGE compare lexical overlap between the reference and generated summaries without taking argumentative structure into account, which is important for legal summaries. In this paper, we propose a novel legal summa
Externí odkaz:
http://arxiv.org/abs/2309.15016
Autor:
Xu, Huihui, Ashley, Kevin
We use the combination of argumentative zoning [1] and a legal argumentative scheme to create legal argumentative segments. Based on the argumentative segmentation, we propose a novel task of classifying argumentative segments of legal case decisions
Externí odkaz:
http://arxiv.org/abs/2307.05081
Publikováno v:
ITiCSE 2023: Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 1. June 2023. Pages 117 - 123
We evaluated the capability of generative pre-trained transformers~(GPT-4) in analysis of textual data in tasks that require highly specialized domain expertise. Specifically, we focused on the task of analyzing court opinions to interpret legal conc
Externí odkaz:
http://arxiv.org/abs/2306.13906
Interpreting the meaning of legal open-textured terms is a key task of legal professionals. An important source for this interpretation is how the term was applied in previous court cases. In this paper, we evaluate the performance of GPT-4 in genera
Externí odkaz:
http://arxiv.org/abs/2306.09525
Autor:
Xu, Huihui, Ashley, Kevin
In this paper, we explore legal argument mining using multiple levels of granularity. Argument mining has usually been conceptualized as a sentence classification problem. In this work, we conceptualize argument mining as a token-level (i.e., word-le
Externí odkaz:
http://arxiv.org/abs/2210.09472
Autor:
Han, Yunfei, Chen, Yuting, Wang, Yong, Zhao, Mingxin, Sun, Xia, Guo, Yemin, Su, Dianbin, Xu, Huihui
Publikováno v:
In Industrial Crops & Products 15 December 2024 222 Part 1
