Zobrazeno 1 - 10
of 452
pro vyhledávání: '"Xianfeng, Gu"'
Publikováno v:
Visual Informatics, Vol 8, Iss 1, Pp 15-25 (2024)
Medical image generation has recently garnered significant interest among researchers. However, the primary generative models, such as Generative Adversarial Networks (GANs), often encounter challenges during training, including mode collapse. To add
Externí odkaz:
https://doaj.org/article/e3dbfe4ea80a409a8d56ed198930b192
Publikováno v:
Axioms, Vol 12, Iss 10, p 942 (2023)
Virtual colonoscopy plays an important role in polyp detection of colorectal cancer. Noise in the colon data acquisition process can result in topological errors during surface reconstruction. Topological denoising can be employed to remove these err
Externí odkaz:
https://doaj.org/article/e467e1ebe2264b4e8e28520d08c7f103
Autor:
Na Lei, Dongsheng An, Yang Guo, Kehua Su, Shixia Liu, Zhongxuan Luo, Shing-Tung Yau, Xianfeng Gu
Publikováno v:
Engineering, Vol 6, Iss 3, Pp 361-374 (2020)
This work introduces an optimal transportation (OT) view of generative adversarial networks (GANs). Natural datasets have intrinsic patterns, which can be summarized as the manifold distribution principle: the distribution of a class of data is close
Externí odkaz:
https://doaj.org/article/2c5a0e46c6fe45fd98c271a0b82e061a
Finding surface mappings with least distortion arises from many applications in various fields. Extremal Teichm\"uller maps are surface mappings with least conformality distortion. The existence and uniqueness of the extremal Teichm\"uller map betw
Externí odkaz:
http://arxiv.org/abs/1307.2679
Publikováno v:
IEEE Transactions on Systems, Man, and Cybernetics: Systems. :1-12
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a691e349bf72c40998e1a18e73635aa7
https://doi.org/10.1109/tsmc.2023.3273896
https://doi.org/10.1109/tsmc.2023.3273896
Autor:
Rongchen Wang, Kai Yin, Muye Ma, Tianli Zhu, Jinzhu Gao, Jie Sun, Xuemei Dong, Chengjun Dong, Xianfeng Gu, He Tian, Chunchang Zhao
Publikováno v:
CCS Chemistry. 4:3715-3723
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::aa177ca7fa9f28c83b204b67528252fc
https://doi.org/10.31635/ccschem.022.202201971
https://doi.org/10.31635/ccschem.022.202201971
Publikováno v:
Computational Visual Media, Vol 4, Iss 1, Pp 33-42 (2018)
Abstract Polycube construction and deformation are essential problems in computer graphics. In this paper, we present a robust, simple, efficient, and automatic algorithm to deform the meshes of arbitrary shapes into polycube form. We derive a clear
Externí odkaz:
https://doaj.org/article/c1164ce9d6414dd1afd7f05e96b3c79b
Publikováno v:
Mathematics, Vol 9, Iss 24, p 3226 (2021)
A very challenging task for action recognition concerns how to effectively extract and utilize the temporal and spatial information of video (especially temporal information). To date, many researchers have proposed various spatial-temporal convoluti
Externí odkaz:
https://doaj.org/article/716eeddd2b814ea9944086e84c24cf54
Publikováno v:
Computational Mathematics and Mathematical Physics. 62:1313-1330
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ce9880c1da6410522c898f846fc1d714
https://doi.org/10.1134/s0965542522080097
https://doi.org/10.1134/s0965542522080097
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 36:10119-10128
Optimal transport (OT) plays an essential role in various areas like machine learning and deep learning. However, computing discrete optimal transport plan for large scale problems with adequate accuracy and efficiency is still highly challenging. Re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::753783fa1893f2c6a856fccf127f7a10
https://doi.org/10.1609/aaai.v36i9.21251
https://doi.org/10.1609/aaai.v36i9.21251