Vote for your favorite mineral in #MinCup25! - Carpathite vs. Tugtupite
Battle of mineralogical oddities as organic mineral #carpathite battles against vs #tugtupite, a mineral that looks like reindeer blood!
Log InRegister
Quick Links : The Mindat ManualThe Rock H. Currier Digital LibraryMindat Newsletter [Free Download]
Home PageAbout MindatThe Mindat ManualHistory of MindatCopyright StatusWho We AreContact UsAdvertise on Mindat
Donate to MindatCorporate SponsorshipSponsor a PageSponsored PagesMindat AdvertisersAdvertise on Mindat
Learning CenterWhat is a mineral?The most common minerals on earthInformation for EducatorsMindat ArticlesThe ElementsThe Rock H. Currier Digital LibraryGeologic Time
Minerals by PropertiesMinerals by ChemistryAdvanced Locality SearchRandom MineralRandom LocalitySearch by minIDLocalities Near MeSearch ArticlesSearch GlossaryMore Search Options
Search For:
Mineral Name:
Locality Name:
Keyword(s):
 
The Mindat ManualAdd a New PhotoRate PhotosLocality Edit ReportCoordinate Completion ReportAdd Glossary Item
Mining CompaniesStatisticsUsersMineral MuseumsClubs & OrganizationsMineral Shows & EventsThe Mindat DirectoryDevice SettingsThe Mineral Quiz
Photo SearchPhoto GalleriesSearch by ColorNew Photos TodayNew Photos YesterdayMembers' Photo GalleriesPast Photo of the Day GalleryPhotography

Luo, Changfan, Xu, Yiping, Shao, Yongkang, Wang, Zihan, Hu, Jianzheng, Yuan, Jiawei, Liu, Yuchen, Duan, Meiyu, Huang, Lan, Zhou, Fengfeng (2023) EvaGoNet: An integrated network of variational autoencoder and Wasserstein generative adversarial network with gradient penalty for binary classification tasks. Information Sciences, 629. 109-122 doi:10.1016/j.ins.2023.01.133

Advanced
   -   Only viewable:
Reference TypeJournal (article/letter/editorial)
TitleEvaGoNet: An integrated network of variational autoencoder and Wasserstein generative adversarial network with gradient penalty for binary classification tasks
JournalInformation Sciences
AuthorsLuo, ChangfanAuthor
Xu, YipingAuthor
Shao, YongkangAuthor
Wang, ZihanAuthor
Hu, JianzhengAuthor
Yuan, JiaweiAuthor
Liu, YuchenAuthor
Duan, MeiyuAuthor
Huang, LanAuthor
Zhou, FengfengAuthor
Year2023 (June)Volume629
PublisherElsevier BV
DOIdoi:10.1016/j.ins.2023.01.133Search in ResearchGate
Generate Citation Formats
Mindat Ref. ID15695041Long-form Identifiermindat:1:5:15695041:3
GUID0
Full ReferenceLuo, Changfan, Xu, Yiping, Shao, Yongkang, Wang, Zihan, Hu, Jianzheng, Yuan, Jiawei, Liu, Yuchen, Duan, Meiyu, Huang, Lan, Zhou, Fengfeng (2023) EvaGoNet: An integrated network of variational autoencoder and Wasserstein generative adversarial network with gradient penalty for binary classification tasks. Information Sciences, 629. 109-122 doi:10.1016/j.ins.2023.01.133
Plain TextLuo, Changfan, Xu, Yiping, Shao, Yongkang, Wang, Zihan, Hu, Jianzheng, Yuan, Jiawei, Liu, Yuchen, Duan, Meiyu, Huang, Lan, Zhou, Fengfeng (2023) EvaGoNet: An integrated network of variational autoencoder and Wasserstein generative adversarial network with gradient penalty for binary classification tasks. Information Sciences, 629. 109-122 doi:10.1016/j.ins.2023.01.133
In(2023) Information Sciences Vol. 629. Elsevier BV

See Also

These are possibly similar items as determined by title/reference text matching only.

Zheng, Ming, Li, Tong, Zhu, Rui, Tang, Yahui, Tang, Mingjing, Lin, Leilei, Ma, Zifei (2020) Conditional Wasserstein generative adversarial network-gradient penalty-based approach to alleviating imbalanced data classification. Information Sciences, 512. 1009-1023 doi:10.1016/j.ins.2019.10.014
Li, Nanjun, Chang, Faliang, Liu, Chunsheng (2023) Human-related anomalous event detection via memory-augmented Wasserstein generative adversarial network with gradient penalty. Pattern Recognition, 138. 109398 doi:10.1016/j.patcog.2023.109398
Lee, Gwo-Chuan, Li, Jyun-Hong, Li, Zi-Yang (2023) A Wasserstein Generative Adversarial Network–Gradient Penalty-Based Model with Imbalanced Data Enhancement for Network Intrusion Detection. Applied Sciences, 13 (14) MDPI AG. 8132 doi:10.3390/app13148132
Xu, Xiaolong, Liu, Xihua, Yin, Xiaochun, Wang, Shoujin, Qi, Quan, Qi, Lianyong (2020) Privacy-aware offloading for training tasks of generative adversarial network in edge computing. Information Sciences, 532. 1-15 doi:10.1016/j.ins.2020.04.026
Liu, Man, Zhou, Wei, Xu, Zeshui (2024) Transformation and learning of the non-equidimensional hesitant fuzzy information based on an extended generative adversarial network. Information Sciences, 664. 120307 doi:10.1016/j.ins.2024.120307
Han, Wei, Wang, Lizhe, Feng, Ruyi, Gao, Lang, Chen, Xiaodao, Deng, Ze, Chen, Jia, Liu, Peng (2020) Sample generation based on a supervised Wasserstein Generative Adversarial Network for high-resolution remote-sensing scene classification. Information Sciences, 539. 177-194 doi:10.1016/j.ins.2020.06.018
Fan, Wenyao, Liu, Gang, Chen, Qiyu, Cui, Zhesi, Yang, Zixiao, Huang, Qianhong, Wu, Xuechao (2023) Geological model automatic reconstruction based on conditioning Wasserstein generative adversarial network with gradient penalty. Earth Science Informatics, 16 (3) 2825-2843 doi:10.1007/s12145-023-01012-9
Mokbal, Fawaz Mahiuob Mohammed, Wang, Dan, Wang, Xiaoxi, Fu, Lihua (2020) Data augmentation-based conditional Wasserstein generative adversarial network-gradient penalty for XSS attack detection system. PeerJ Computer Science, 6. doi:10.7717/peerj-cs.328
Yin, Hai, Yang, Qihang, Huang, Fangyuan, Li, Hongjie, Wang, Hui, Zheng, Huadan, Huang, Furong (2025) Multimodal fish maw type recognition based on Wasserstein generative adversarial network combined with gradient penalty and spectral fusion. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 327. doi:10.1016/j.saa.2024.125430
Zhang, Ke, Hao, Wenning, Yu, Xiaohan, Shao, Tianhao (2024) An interpretable image classification model Combining a fuzzy neural network with a variational autoencoder inspired by the human brain. Information Sciences, 661. 119885 doi:10.1016/j.ins.2023.119885
Leng, Jiancai, Zhu, Jianqun, Yan, Yihao, Yu, Xin, Liu, Ming, Lou, Yitai, Liu, Yanbing, Gao, Licai, Sun, Yuan, He, Tianzheng, Yang, Qingbo, Feng, Chao, Wang, Dezheng, Zhang, Yang, Xu, Qing, Xu, Fangzhou (2024) Multilevel Laser-Induced Pain Measurement with Wasserstein Generative Adversarial Network — Gradient Penalty Model. International Journal of Neural Systems, 34 (1) doi:10.1142/s0129065723500673
 
and/or  
Mindat.org is an outreach project of the Hudson Institute of Mineralogy, a 501(c)(3) not-for-profit organization.
Copyright © mindat.org and the Hudson Institute of Mineralogy 1993-2025, except where stated. Most political location boundaries are © OpenStreetMap contributors. Mindat.org relies on the contributions of thousands of members and supporters. Founded in 2000 by Jolyon Ralph.
To cite: Ralph, J., Von Bargen, D., Martynov, P., Zhang, J., Que, X., Prabhu, A., Morrison, S. M., Li, W., Chen, W., & Ma, X. (2025). Mindat.org: The open access mineralogy database to accelerate data-intensive geoscience research. American Mineralogist, 110(6), 833–844. doi:10.2138/am-2024-9486.
Privacy Policy - Terms & Conditions - Contact Us / DMCA issues - Report a bug/vulnerability Current server date and time: September 20, 2025 08:50:03
Go to top of page