Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Xiao-Yi Luo"'
Autor:
Meiwen Yang, Zhi-Qi Guo, Xiao-Yi Luo, Zhao-Qiang Shen, Zi-Qing Xia, Chih-Ting Lu, Yue-Lin Sming Tsai, Yi-Zhong Fan
Publikováno v:
Journal of High Energy Physics, Vol 2024, Iss 10, Pp 1-33 (2024)
Abstract This study reanalyzes the detection prospects of dark matter (DM) annihilation signals in the Galactic Center, focusing on velocity-dependent dynamics within a spike density near the supermassive black hole (Sgr A⋆). We investigate three a
Externí odkaz:
https://doaj.org/article/095b4f9542a042fba30d435d42abd204
Publikováno v:
Frontiers of Information Technology & Electronic Engineering. 21:1005-1018
Image classification is an important application of deep learning. In a typical classification task, the classification accuracy is strongly related to the features that are extracted via deep learning methods. An autoencoder is a special type of neu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5b3f58a377650a0aeae118a53e61ddd8
https://doi.org/10.1631/fitee.1900116
https://doi.org/10.1631/fitee.1900116
Publikováno v:
Mathematical Problems in Engineering, Vol 2019 (2019)
In real applications, label noise and feature noise are two main noise sources. Similar to feature noise, label noise imposes great detriment on training classification models. Motivated by successful application of deep learning method in normal cla
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c3769b178527f3d42f841305c812c96c
Publikováno v:
Chemometrics and Intelligent Laboratory Systems. 192:103814
Nowadays, some traditional autoencoders and their extensions have been widely applied in data-driven fault diagnosis for feature extraction. However, because of the fact that traditional autoencoders could not make use of label information, the repre
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eb23c84aa5677d6b500cdf271b6f19d6
https://doi.org/10.1016/j.chemolab.2019.103814
https://doi.org/10.1016/j.chemolab.2019.103814