Výsledky vyhledávání - "semi-supervised variational autoencoder"

A Semi-Supervised Variational Autoencoder for Fault Detection of Low-Severity Inter-Turn Short-Circuit in PMSMs

Autoři: Mingda Zhu Du Nguyen Peihua Han a další

Zdroj: 2025 IEEE Workshop on Electrical Machines Design, Control and Diagnosis (WEMDCD). :1-6

A mechanical fault diagnosis model with semi-supervised variational autoencoder based on long short-term memory network

Autoři: Yuanyuan Qu Tao Li Shichen Fu a další

Zdroj: Nonlinear Dynamics. 113:459-478

Semi-Supervised Variational Autoencoder for Cell Feature Extraction In Multiplexed Immunofluorescence Images

Autoři: Sandarenu, Piumi Chen, Julia Slapetova, Iveta a další

Zdroj: 2024 IEEE International Symposium on Biomedical Imaging (ISBI). :1-5

Témata: FOS: Computer and information sciences, Computer Vision and Pattern Recognition (cs.CV), Image and Video Processing (eess.IV), Computer Science - Computer Vision and Pattern Recognition, FOS: Electrical engineering, electronic engineering, information engineering, Electrical Engineering and Systems Science - Image and Video Processing, 3. Good health

Přístupová URL adresa: http://arxiv.org/abs/2406.15727

Customization of latent space in semi-supervised Variational AutoEncoder

Autoři: Seunghwan An Jong-June Jeon

Zdroj: Pattern Recognition Letters. 177:54-60

Using Semi‐supervised Variational Autoencoder and Acute fMRI Changes to Predict Antidepressant Treatment Responses Among Older Adults with Depression

Autoři: Linghai Wang Jihui Lee Akiko Mizuno a další

Zdroj: Alzheimer's & Dementia. 19

Témata: 03 medical and health sciences, 0302 clinical medicine, 3. Good health

A Joint Semi-Supervised Variational Autoencoder and Transfer Learning Model for Designing Molecular Transition Metal Complexes

Autoři: Tzuhsiung Yang Tzu-Hang Lee Yu-Ting Chen a další

Interpretable Operational Risk Classification with Semi-Supervised Variational Autoencoder

Autoři: Yi Yang Fan Zhou Shengming Zhang

Zdroj: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. :846-852

Témata: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Přístupová URL adresa: https://www.aclweb.org/anthology/2020.acl-main.78.pdf

An Improved Semi-supervised Variational Autoencoder with Gate Mechanism for Text Classification

Autoři: Haiming Ye Weiwen Zhang Mengna Nie

Zdroj: International Journal of Pattern Recognition and Artificial Intelligence. 36

Témata: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Semi-supervised Variational Autoencoder for WiFi Indoor Localization

Autoři: Leonid Antsfeld Boris Chidlovskii

Zdroj: 2019 International Conference on Indoor Positioning and Indoor Navigation (IPIN). :1-8

Témata: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Přístupová URL adresa: https://dblp.uni-trier.de/db/conf/ipin/ipin2019.html#ChidlovskiiA19
https://lens.org/012-936-148-987-467

Semi-supervised Variational Autoencoder for Survival Prediction

Autoři: Pálsson, Sveinn Cerri, Stefano Dittadi, Andrea a další

Přispěvatelé: Pálsson, Sveinn Cerri, Stefano Dittadi, Andrea a další

Zdroj: Lecture Notes in Computer Science ISBN: 9783030466428
Pálsson, S, Cerri, S, Dittadi, A & Leemput, K V 2020, Semi-supervised variational autoencoder for survival prediction . in A Crimi & S Bakas (eds), Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries . Springer, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11993 LNCS, pp. 124-134, 5th International MICCAI Brainlesion Workshop, held in conjunction with the Medical Image Computing for Computer Assisted Intervention, Shenzhen, China, 17/10/2019 . https://doi.org/10.1007/978-3-030-46643-5_12
International MICCAI Brainlesion Workshop
Lecture Notes in Computer Science
Lecture Notes in Computer Science-Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries

Témata: FOS: Computer and information sciences, Computer Vision and Pattern Recognition (cs.CV), Computer Science - Computer Vision and Pattern Recognition, 0202 electrical engineering, electronic engineering, information engineering, Deep generative models, Semi-supervised VAE, 02 engineering and technology, 01 natural sciences, Survival time, 0105 earth and related environmental sciences

Popis souboru: application/pdf

Přístupová URL adresa: http://arxiv.org/pdf/1910.04488
http://arxiv.org/abs/1910.04488
https://dblp.uni-trier.de/db/journals/corr/corr1910.html#abs-1910-04488
https://link.springer.com/chapter/10.1007/978-3-030-46643-5_12
https://rd.springer.com/chapter/10.1007/978-3-030-46643-5_12
http://dblp.uni-trier.de/db/journals/corr/corr1910.html#abs-1910-04488
https://arxiv.org/pdf/1910.04488.pdf
https://arxiv.org/abs/1910.04488
https://ui.adsabs.harvard.edu/abs/2019arXiv191004488P/abstract
https://arxiv.org/pdf/1910.04488v1
https://arxiv.org/abs/1910.04488
https://orbit.dtu.dk/en/publications/51b23f33-01a0-4c7e-8c48-40dfbb838cc8

Semi-supervised variational autoencoder for survival prediction

Autoři: Crimi, Alessandro Bakas, Spyridon Pálsson, Sveinn a další

Zdroj: Pálsson , S , Cerri , S , Dittadi , A & Leemput , K V 2020 , Semi-supervised variational autoencoder for survival prediction . in A Crimi & S Bakas (eds) , Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries . Springer , Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) , vol. 11993 LNCS , pp. 124-134 , 5th International MICCAI Brainlesion Workshop, held in conjunction with the Medical Image Computing for Computer Assisted Intervention , Shenzhen , China , 17/10/2019 .

Témata: Deep generative models, Semi-supervised VAE, Survival time, contributionToPeriodical

URL: https://orbit.dtu.dk/en/publications/51b23f33-01a0-4c7e-8c48-40dfbb838cc8
https://doi.org/10.1007/978-3-030-46643-5_12
https://backend.orbit.dtu.dk/ws/files/217837891/1910.04488.pdf

Semi-supervised Variational Autoencoder for Regression: Application on Soft Sensors

Autoři: Zhuang, Yilin Zhou, Zhuobin Alakent, Burak a další

Témata: Computer Science - Machine Learning, text

URL: http://arxiv.org/abs/2211.05979

Semi-Supervised Variational Autoencoder for Survival Prediction

Autoři: Pálsson, Sveinn Cerri, Stefano Dittadi, Andrea a další

Témata: Computer Science - Computer Vision and Pattern Recognition, text

URL: http://arxiv.org/abs/1910.04488

Interpretable Operational Risk Classification with Semi-supervised Variational Autoencoder

Autoři: Fan, Zhou Zhang, Shengming Yang, Yi

Témata: Conference paper

URL: http://repository.ust.hk/ir/Record/1783.1-104743
http://lbdiscover.ust.hk/uresolver?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rfr_id=info:sid/HKUST:SPI&rft.genre=article&rft.issn=&rft.volume=&rft.issue=&rft.date=2020&rft.spage=&rft.aulast=Fan&rft.aufirst=Zhou&rft.atitle=Interpretable+Operational+Risk+Classification+with+Semi-supervised+Variational+Autoencoder&rft.title=
http://gateway.isiknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=LinksAMR&SrcApp=PARTNER_APP&DestLinkType=FullRecord&DestApp=WOS&KeyUT=000570978201013

Interpretable Operational Risk Classification with Semi-supervised Variational Autoencoder

Autoři: Zhou, Fan Zhang, Shengming Yang, Yi

Témata: Conference paper

URL: http://repository.hkust.edu.hk/ir/Record/1783.1-104743
https://doi.org/10.18653/v1/2020.acl-main.78
http://lbdiscover.ust.hk/uresolver?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rfr_id=info:sid/HKUST:SPI&rft.genre=article&rft.issn=&rft.volume=&rft.issue=&rft.date=2020&rft.spage=&rft.aulast=Fan&rft.aufirst=Zhou&rft.atitle=Interpretable+Operational+Risk+Classification+with+Semi-supervised+Variational+Autoencoder&rft.title=
http://gateway.isiknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=LinksAMR&SrcApp=PARTNER_APP&DestLinkType=FullRecord&DestApp=WOS&KeyUT=000570978201013
http://www.scopus.com/record/display.url?eid=2-s2.0-85106173384&origin=inward

Semi-supervised variational autoencoder for indoor localization

Developing semi-supervised variational autoencoder-generative adversarial network models to enhance quality prediction performance

Autoři: Kai Wang Sai Kit Ooi Junghui Chen a další

Zdroj: Chemometrics and Intelligent Laboratory Systems. 217:104385

Témata: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 0210 nano-technology

Přístupová URL adresa: https://www.sciencedirect.com/science/article/pii/S0169743921001532

A mechanical fault diagnosis model with semi-supervised variational autoencoder based on long short-term memory network.

Autoři: Qu, Yuanyuan Li, Tao Fu, Shichen a další

Zdroj: Nonlinear Dynamics; Jan2025, Vol. 113 Issue 1, p459-478, 20p

Semi-Supervised Variational Autoencoder for Indoor Localization

Using Semi‐supervised Variational Autoencoder and Acute fMRI Changes to Predict Antidepressant Treatment Responses Among Older Adults with Depression.

Autoři: Wang, Linghai Lee, Jihui Mizuno, Akiko a další

Zdroj: Alzheimer's & Dementia: The Journal of the Alzheimer's Association. Dec2023 Supplement 17, Vol. 19, p1-2. 2p.