Data-driven Parameterizable Generative Adversarial Networks for Synthetic Data Augmentation of Guided Ultrasonic Wave Sensor Signals

被引:0
|
作者
Bosse, Stefan [1 ,2 ]
机构
[1] Univ. of Bremen, Dept. Computer Science, Bremen, Germany
[2] Univ. of Siegen, Dept. Mech. Engineering, Siegen, Germany
来源
e-Journal of Nondestructive Testing | 2024年 / 29卷 / 07期
关键词
12;
D O I
10.58286/29787
中图分类号
学科分类号
摘要
引用
收藏
相关论文
共 50 条
  • [41] Data Augmentation with Generative Adversarial Networks for Grocery Product Image Recognition
    Wei, Yuchen
    Xu, Shuxiang
    Son Tran
    Kang, Byeong
    16TH IEEE INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION, ROBOTICS AND VISION (ICARCV 2020), 2020, : 963 - 968
  • [42] Auxiliary Conditional Generative Adversarial Networks for Image Data Set Augmentation
    Mudavathu, Kalpana Devi Bai
    Rao, V. P. Chandra Sekhara
    Ramana, K., V
    PROCEEDINGS OF THE 2018 3RD INTERNATIONAL CONFERENCE ON INVENTIVE COMPUTATION TECHNOLOGIES (ICICT 2018), 2018, : 263 - 269
  • [43] Using Generative Adversarial Networks for Data Augmentation in Android Malware Detection
    Chen, Yi-Ming
    Yang, Chun-Hsien
    Chen, Guo-Chung
    2021 IEEE CONFERENCE ON DEPENDABLE AND SECURE COMPUTING (DSC), 2021,
  • [44] Conditional Generative Adversarial Networks for Data Augmentation of a Neonatal Image Dataset
    Lyra, Simon
    Mustafa, Arian
    Rixen, Joeran
    Borik, Stefan
    Lueken, Markus
    Leonhardt, Steffen
    SENSORS, 2023, 23 (02)
  • [45] Continuous conditional generative adversarial networks for data-driven solutions of poroelasticity with heterogeneous material properties
    Kadeethum, T.
    O'Malley, D.
    Choi, Y.
    Viswanathan, H. S.
    Bouklas, N.
    Yoon, H.
    COMPUTERS & GEOSCIENCES, 2022, 167
  • [46] A framework for data-driven solution and parameter estimation of PDEs using conditional generative adversarial networks
    Teeratorn Kadeethum
    Daniel O’Malley
    Jan Niklas Fuhg
    Youngsoo Choi
    Jonghyun Lee
    Hari S. Viswanathan
    Nikolaos Bouklas
    Nature Computational Science, 2021, 1 : 819 - 829
  • [47] IE-GAN: a data-driven crowd simulation method via generative adversarial networks
    Xuanqi Lin
    Yuchen Liang
    Yong Zhang
    Yongli Hu
    Baocai Yin
    Multimedia Tools and Applications, 2024, 83 : 45207 - 45240
  • [48] Data augmentation using generative adversarial networks for robust speech recognition
    Qian, Yanmin
    Hu, Hu
    Tan, Tian
    SPEECH COMMUNICATION, 2019, 114 : 1 - 9
  • [49] Data-driven Full-waveform Inversion Surrogate using Conditional Generative Adversarial Networks
    Saraiva, Marcus
    Forechi, Avelino
    Neto, Jorcy de Oliveira
    DelRey, Antonio
    Rauber, Thomas
    2021 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2021,
  • [50] Data Augmentation Based on Generative Adversarial Networks for Endoscopic Image Classification
    Park, Hyun-Cheol
    Hong, In-Pyo
    Poudel, Sahadev
    Choi, Chang
    IEEE ACCESS, 2023, 11 : 49216 - 49225