Zobrazeno 1 - 10
of 196
pro vyhledávání: '"Huang, Biqing"'
Autor:
Jiao, Guanlong, Zhang, Chenyangguang, Yin, Haonan, Mo, Yu, Huang, Biqing, Pan, Hui, Luo, Yi, Liu, Jingxian
Domain generalized semantic segmentation is an essential computer vision task, for which models only leverage source data to learn the capability of generalized semantic segmentation towards the unseen target domains. Previous works typically address
Externí odkaz:
http://arxiv.org/abs/2404.13701
In the context of flexible manufacturing systems that are required to produce different types and quantities of products with minimal reconfiguration, this paper addresses the problem of unsupervised multi-class anomaly detection: develop a unified m
Externí odkaz:
http://arxiv.org/abs/2307.08059
Autor:
Li, Hefei, Niu, Yanchang, Yin, Haonan, Mo, Yu, Liu, Yi, Huang, Biqing, Wu, Ruibin, Liu, Jingxian
Publikováno v:
In Advanced Engineering Informatics October 2024 62 Part C
Publikováno v:
In Neurocomputing 7 May 2024 581
Autor:
HUANG Biqing, LI Lanjuan
Publikováno v:
Xiehe Yixue Zazhi, Vol 14, Iss 5, Pp 939-944 (2023)
Vaccine is the most effective method to prevent the spread of communicable diseases, but the immune response it induces varies significantly among individuals and populations in different regions. Recent studies have shown that the composition and fu
Externí odkaz:
https://doaj.org/article/0709db4beb144696902b6a35045027b8
Publikováno v:
In IJCAI, pages 3926-3932, 2020
Prior works in cross-lingual named entity recognition (NER) with no/little labeled data fall into two primary categories: model transfer based and data transfer based methods. In this paper we find that both method types can complement each other, in
Externí odkaz:
http://arxiv.org/abs/2007.07683
Publikováno v:
In ACL, pages 6505-6514, 2020
To better tackle the named entity recognition (NER) problem on languages with little/no labeled data, cross-lingual NER must effectively leverage knowledge learned from source languages with rich labeled data. Previous works on cross-lingual NER are
Externí odkaz:
http://arxiv.org/abs/2004.12440
Autor:
Wu, Qianhui, Lin, Zijia, Wang, Guoxin, Chen, Hui, Karlsson, Börje F., Huang, Biqing, Lin, Chin-Yew
Publikováno v:
In AAAI, pages 9274-9281, 2020
For languages with no annotated resources, transferring knowledge from rich-resource languages is an effective solution for named entity recognition (NER). While all existing methods directly transfer from source-learned model to a target language, i
Externí odkaz:
http://arxiv.org/abs/1911.06161
Publikováno v:
In Engineering Applications of Artificial Intelligence August 2023 123 Part A
Autor:
Lu, Bingyu1 (AUTHOR), Huang, Biqing1 (AUTHOR) hbq@tsinghua.edu.cn
Publikováno v:
Journal of Intelligent Manufacturing. Mar2024, Vol. 35 Issue 3, p1267-1280. 14p.