Diagnostic-quality guided wave signals synthesized using generative adversarial neural networks

HIGHLIGHTS

  • who: Mateusz Heesch and collaborators from the Department of Robotics and Mechatronics, AGH University of Science and Technology, AlAMickiewicza , have published the article: Diagnostic-Quality Guided Wave Signals Synthesized Using Generative Adversarial Neural Networks, in the Journal: Sensors 2022, 22, 3848. of /2022/
  • what: This research is intended to provide background for future StyleGAN applications to synthesize particular types of data for GW-based damage detection, including previously unseen sensor locations or generation of artificial damage in various structures. While a detailed and comprehensive discussion of different approaches to this problem is beyond the scope . . .

     

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