146 related articles for article (PubMed ID: 38684097)
1. Machine Learning Data Augmentation Strategy for Electron Energy Loss Spectroscopy: Generative Adversarial Networks.
Del-Pozo-Bueno D; Kepaptsoglou D; Ramasse QM; Peiró F; Estradé S
Microsc Microanal; 2024 Apr; 30(2):278-293. PubMed ID: 38684097
[TBL] [Abstract][Full Text] [Related]
2. Utilization of Synthetic Near-Infrared Spectra via Generative Adversarial Network to Improve Wood Stiffness Prediction.
Ali SD; Raut S; Dahlen J; Schimleck L; Bergman R; Zhang Z; Nasir V
Sensors (Basel); 2024 Mar; 24(6):. PubMed ID: 38544255
[TBL] [Abstract][Full Text] [Related]
3. Comparative of machine learning classification strategies for electron energy loss spectroscopy: Support vector machines and artificial neural networks.
Del-Pozo-Bueno D; Kepaptsoglou D; Peiró F; Estradé S
Ultramicroscopy; 2023 Nov; 253():113828. PubMed ID: 37556961
[TBL] [Abstract][Full Text] [Related]
4. Cotton Fusarium wilt diagnosis based on generative adversarial networks in small samples.
Zhang Z; Ma L; Wei C; Yang M; Qin S; Lv X; Zhang Z
Front Plant Sci; 2023; 14():1290774. PubMed ID: 38162306
[TBL] [Abstract][Full Text] [Related]
5. Data augmentation using Generative Adversarial Networks (GANs) for GAN-based detection of Pneumonia and COVID-19 in chest X-ray images.
Motamed S; Rogalla P; Khalvati F
Inform Med Unlocked; 2021; 27():100779. PubMed ID: 34841040
[TBL] [Abstract][Full Text] [Related]
6. 3D human pose data augmentation using Generative Adversarial Networks for robotic-assisted movement quality assessment.
Wang X; Mi Y; Zhang X
Front Neurorobot; 2024; 18():1371385. PubMed ID: 38644903
[TBL] [Abstract][Full Text] [Related]
7. Optimizing Latent Distributions for Non-Adversarial Generative Networks.
Guo T; Xu C; Shi B; Xu C; Tao D
IEEE Trans Pattern Anal Mach Intell; 2022 May; 44(5):2657-2672. PubMed ID: 33301400
[TBL] [Abstract][Full Text] [Related]
8. fNIRS-GANs: data augmentation using generative adversarial networks for classifying motor tasks from functional near-infrared spectroscopy.
Nagasawa T; Sato T; Nambu I; Wada Y
J Neural Eng; 2020 Feb; 17(1):016068. PubMed ID: 31945755
[TBL] [Abstract][Full Text] [Related]
9. Combating COVID-19 Using Generative Adversarial Networks and Artificial Intelligence for Medical Images: Scoping Review.
Ali H; Shah Z
JMIR Med Inform; 2022 Jun; 10(6):e37365. PubMed ID: 35709336
[TBL] [Abstract][Full Text] [Related]
10. Improving Speech Emotion Recognition With Adversarial Data Augmentation Network.
Yi L; Mak MW
IEEE Trans Neural Netw Learn Syst; 2022 Jan; 33(1):172-184. PubMed ID: 33035171
[TBL] [Abstract][Full Text] [Related]
11. The Deep Learning Generative Adversarial Random Neural Network in data marketplaces: The digital creative.
Serrano W
Neural Netw; 2023 Aug; 165():420-434. PubMed ID: 37331232
[TBL] [Abstract][Full Text] [Related]
12. Data Augmentation Techniques for Machine Learning Applied to Optical Spectroscopy Datasets in Agrifood Applications: A Comprehensive Review.
Gracia Moisés A; Vitoria Pascual I; Imas González JJ; Ruiz Zamarreño C
Sensors (Basel); 2023 Oct; 23(20):. PubMed ID: 37896655
[TBL] [Abstract][Full Text] [Related]
13. Generative adversarial network based synthetic data training model for lightweight convolutional neural networks.
Rather IH; Kumar S
Multimed Tools Appl; 2023 May; ():1-23. PubMed ID: 37362646
[TBL] [Abstract][Full Text] [Related]
14. Data augmentation for enhancing EEG-based emotion recognition with deep generative models.
Luo Y; Zhu LZ; Wan ZY; Lu BL
J Neural Eng; 2020 Oct; 17(5):056021. PubMed ID: 33052888
[TBL] [Abstract][Full Text] [Related]
15. A Generative Adversarial Network (GAN) Technique for Internet of Medical Things Data.
Vaccari I; Orani V; Paglialonga A; Cambiaso E; Mongelli M
Sensors (Basel); 2021 May; 21(11):. PubMed ID: 34071944
[TBL] [Abstract][Full Text] [Related]
16. Empowering precise advertising with Fed-GANCC: A novel federated learning approach leveraging Generative Adversarial Networks and group clustering.
Su C; Wei J; Lei Y; Xuan H; Li J
PLoS One; 2024; 19(4):e0298261. PubMed ID: 38598458
[TBL] [Abstract][Full Text] [Related]
17. Creating Artificial Images for Radiology Applications Using Generative Adversarial Networks (GANs) - A Systematic Review.
Sorin V; Barash Y; Konen E; Klang E
Acad Radiol; 2020 Aug; 27(8):1175-1185. PubMed ID: 32035758
[TBL] [Abstract][Full Text] [Related]
18. Biosignal Data Augmentation Based on Generative Adversarial Networks.
Haradal S; Hayashi H; Uchida S
Annu Int Conf IEEE Eng Med Biol Soc; 2018 Jul; 2018():368-371. PubMed ID: 30440412
[TBL] [Abstract][Full Text] [Related]
19. Augmentation of Doppler Radar Data Using Generative Adversarial Network for Human Motion Analysis.
Alnujaim I; Kim Y
Healthc Inform Res; 2019 Oct; 25(4):344-349. PubMed ID: 31777679
[TBL] [Abstract][Full Text] [Related]
20. Generative Adversarial Networks in Digital Histopathology: Current Applications, Limitations, Ethical Considerations, and Future Directions.
Alajaji SA; Khoury ZH; Elgharib M; Saeed M; Ahmed ARH; Khan MB; Tavares T; Jessri M; Puche AC; Hoorfar H; Stojanov I; Sciubba JJ; Sultan AS
Mod Pathol; 2024 Jan; 37(1):100369. PubMed ID: 37890670
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]