Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Zhongtian Hu"'
Publikováno v:
Separations, Vol 9, Iss 12, p 451 (2022)
Micro-scale fluids are tiny droplets that adhere to the surface of an object as a result of rainfall, perspiration, etc. Micro-scale fluid simulation is widely used in fields such as film and games. The existing state-of-the-art simulation methods ar
Externí odkaz:
https://doaj.org/article/f473c59315a54be78eec12f205465994
Publikováno v:
Computational Intelligence. 38:1831-1858
Publikováno v:
Neural Computing and Applications. 34:11831-11851
Autor:
Xujia Qin, Zhongtian Hu
Publikováno v:
Multimedia Tools and Applications. 80:5773-5807
The manual modeling of ancient Chinese architecture is long and tedious work for artists due to the strict and complex construction rules. Existing procedural modeling methods can reduce the modeling workload; however, only limited types of ancient b
Publikováno v:
Intelligent Computing Methodologies ISBN: 9783031138317
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d9dceb615b5e6fa16e9ef6f296efaefc
https://doi.org/10.1007/978-3-031-13832-4_20
https://doi.org/10.1007/978-3-031-13832-4_20
Publikováno v:
Knowledge-Based Systems. 259:110069
Autor:
Tengsheng Jiang, Yuhui Chen, Shixuan Guan, Zhongtian Hu, Weizhong Lu, Qiming Fu, Yijie Ding, Haiou Li, Hongjie Wu
Publikováno v:
IEEE/ACM Transactions on Computational Biology and Bioinformatics. :1-1
G protein-coupled receptors (GPCRs) account for about 40% to 50% of drug targets. Many human diseases are related to G protein coupled receptors. Accurate prediction of GPCR interaction is not only essential to understand its structural role, but als
Publikováno v:
IEEE Access, Vol 10, Pp 129480-129489 (2022)
In order to solve the problem of low accuracy and efficiency in printed circuit board(PCB) defect detection using reference methods, a Transformer-YOLO network detection model is proposed. Firstly, an improved clustering algorithm is used to generate
Externí odkaz:
https://doaj.org/article/a98e6113547048ff979ff3706a204da7