Improving Artifact Detection in Endoscopic Video Frames Using Deep Learning Techniques

Chavarrias-Solano, PE, Ali-Teevno, M, Ochoa-Ruiz, G et al. (1 more author) (2022) Improving Artifact Detection in Endoscopic Video Frames Using Deep Learning Techniques. In: Advances in Computational Intelligence 21st Mexican International Conference on Artificial Intelligence, MICAI 2022, Monterrey, Mexico, October 24–29, 2022, Proceedings, Part I. 21st Mexican International Conference on Artificial Intelligence, MICAI 2022, 24-29 Oct 2022, Monterrey, Mexico. Springer , pp. 327-338. ISBN 9783031194924

Abstract

Metadata

Item Type: Proceedings Paper
Authors/Creators:
Keywords: Deep learning ; Object detection; YOLO; YOLACT; Endoscopic artifact detection
Dates:
  • Published: 23 October 2022
  • Published (online): 23 October 2022
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 20 Dec 2022 13:51
Last Modified: 20 Dec 2022 13:51
Published Version: http://dx.doi.org/10.1007/978-3-031-19493-1_26
Status: Published
Publisher: Springer
Identification Number: 10.1007/978-3-031-19493-1_26
Open Archives Initiative ID (OAI ID):

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