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
  • [11] Generative Adversarial Networks as an Advanced Data Augmentation Technique for MRI Data
    Konidaris, Filippos
    Tagaris, Thanos
    Sdraka, Maria
    Stafylopatis, Andreas
    PROCEEDINGS OF THE 14TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER VISION, IMAGING AND COMPUTER GRAPHICS THEORY AND APPLICATIONS (VISAPP), VOL 5, 2019, : 48 - 59
  • [12] DCNN Augmentation via Synthetic Data from Variational Autoencoders and Generative Adversarial Networks
    Kornish, David
    Ezekiel, Soundararajan
    Cornacchia, Maria
    2018 IEEE APPLIED IMAGERY PATTERN RECOGNITION WORKSHOP (AIPR), 2018,
  • [13] Data-driven concurrent nanostructure optimization based on conditional generative adversarial networks
    Baucour, Arthur
    Kim, Myungjoon
    Shin, Jonghwa
    NANOPHOTONICS, 2022, 11 (12) : 2865 - 2873
  • [14] Fast Data-Driven Simulation of Cherenkov Detectors Using Generative Adversarial Networks
    Maevskiy, A.
    Derkach, D.
    Kazeev, N.
    Ustyuzhanin, A.
    Artemev, M.
    Anderlini, L.
    19TH INTERNATIONAL WORKSHOP ON ADVANCED COMPUTING AND ANALYSIS TECHNIQUES IN PHYSICS RESEARCH, 2020, 1525
  • [15] Data-driven Method of Renewable Energy Based on Generative Adversarial Networks and EnergyPLAN
    Yang, Liu
    Zhang, Huaguang
    Mu, Yunfei
    Sun, S.
    Wu, Z.
    PROCEEDINGS OF THE 33RD CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2021), 2021, : 938 - 943
  • [16] Data-Driven Enhancement of Blurry Retinal Images via Generative Adversarial Networks
    Zhao, He
    Yang, Bingyu
    Cao, Lvchen
    Li, Huiqi
    MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION - MICCAI 2019, PT I, 2019, 11764 : 75 - 83
  • [17] Data-driven modeling of noise time series with convolutional generative adversarial networks *
    Wunderlich, Adam
    Sklar, Jack
    MACHINE LEARNING-SCIENCE AND TECHNOLOGY, 2023, 4 (03):
  • [18] Creation of Synthetic Data with Conditional Generative Adversarial Networks
    Vega-Marquez, Belen
    Rubio-Escudero, Cristina
    Riquelme, Jose C.
    Nepomuceno-Chamorro, Isabel
    14TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING MODELS IN INDUSTRIAL AND ENVIRONMENTAL APPLICATIONS (SOCO 2019), 2020, 950 : 231 - 240
  • [19] Generation of Synthetic Data with Conditional Generative Adversarial Networks
    Vega-Marquez, Belen
    Rubio-Escudero, Cristina
    Nepomuceno-Chamorro, Isabel
    LOGIC JOURNAL OF THE IGPL, 2022, 30 (02) : 252 - 262
  • [20] Wasserstein Generative Adversarial Networks Based Data Augmentation for Radar Data Analysis
    Lee, Hansoo
    Kim, Jonggeun
    Kim, Eun Kyeong
    Kim, Sungshin
    APPLIED SCIENCES-BASEL, 2020, 10 (04):