Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Chongwen Liu"'
Autor:
Chenshu Liu, Songbin Ben, Chongwen Liu, Xianchao Li, Qingxia Meng, Yilin Hao, Qian Jiao, Pinyi Yang
Publikováno v:
Heritage Science, Vol 12, Iss 1, Pp 1-13 (2024)
Abstract Purpose Paper-based artifacts hold significant cultural and social values. However, paper is intrinsically fragile to microorganisms, such as mold, due to its cellulose composition, which can serve as a microorganisms’ nutrient source. Mol
Externí odkaz:
https://doaj.org/article/6eee744f35f749819d196ee9b02d410d
Publikováno v:
Heritage Science, Vol 10, Iss 1, Pp 1-9 (2022)
Abstract The ancient lacquer films excavated from Dongshan Han tomb M6 of the Western Han Dynasty in Taiyuan City, Shanxi, China, were found sensitive to pH variation. This paper aims to demonstrate the pH-dependent warping behaviors of the ancient l
Externí odkaz:
https://doaj.org/article/d1ee89e2bda04088bfd0870145644ae4
Publikováno v:
Frontiers in Neurorobotics, Vol 16 (2023)
Finger-vein biometrics has been extensively investigated for personal verification. Single sample per person (SSPP) finger-vein recognition is one of the open issues in finger-vein recognition. Despite recent advances in deep neural networks for fing
Externí odkaz:
https://doaj.org/article/4fb937e0bfdc45fea15a03532b30a27c
Autor:
Huyong Yan, Li Feng, You Yu, Weiling Liao, Lei Feng, Jingyue Zhang, Dan Liu, Ying Zou, Chongwen Liu, Linfa Qu, Xiaoman Zhang
Publikováno v:
Frontiers in Computational Neuroscience, Vol 16 (2022)
Cross-site scripting (XSS) attacks are currently one of the most threatening network attack methods. Effectively detecting and intercepting XSS attacks is an important research topic in the network security field. This manuscript proposes a convoluti
Externí odkaz:
https://doaj.org/article/cb902b27ca7045deaddb317046ab99e3
Publikováno v:
2022 International Conference on Cyber-Physical Social Intelligence (ICCSI).
Autor:
Chongwen Liu, Qun Song
Publikováno v:
2022 the 5th International Conference on Big Data and Internet of Things.
Publikováno v:
IEEE Transactions on Information Forensics and Security. 16:2652-2666
Despite recent advances of deep neural networks in hand vein identification, the existing solutions assume the availability of a large and rich set of training image samples. These solutions, therefore, still lack the capability to extract robust and
Publikováno v:
Communications in Computer and Information Science ISBN: 9789811692468
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bd1ee19ca600f3a126cbe974bd35e619
https://doi.org/10.1007/978-981-16-9247-5_20
https://doi.org/10.1007/978-981-16-9247-5_20
Publikováno v:
2021 International Conference on Cyber-Physical Social Intelligence (ICCSI).
Publikováno v:
Neurocomputing. 208:80-98
Using images that are dispersed in a network can improve image classification performance; however, it is easy to leak the image holders' privacy. In this paper, we present a novel method that considers both image classification performance and the i