External Links

Cite Key

Statistics

  • References: 0
  • Cited by: 0
  • Reviews: 0
  • Bibliographies: 0

PDF

Researchr

Researchr is a web site for finding, collecting, sharing, and reviewing scientific publications, for researchers by researchers.

Sign up for an account to create a profile with publication list, tag and review your related work, and share bibliographies with your co-authors.

Low-Rank Constrained Multichannel Signal Denoising Considering Channel-Dependent Sensitivity Inspired by Self-Supervised Learning for Optical Fiber Sensing

Noriyuki Tonami, Wataru Kohno, Sakiko Mishima, Yumi Arai, Reishi Kondo, Tomoyuki Hino. Low-Rank Constrained Multichannel Signal Denoising Considering Channel-Dependent Sensitivity Inspired by Self-Supervised Learning for Optical Fiber Sensing. In IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2024, Seoul, Republic of Korea, April 14-19, 2024. pages 8511-8515, IEEE, 2024. [doi]

Abstract

Abstract is missing.

runs on