Implementation of Continuous Signal Pre-Processing Methods For Segmentation

Dilnaz Zhaxylykova*, Ibraheem Shayea, Abdulraqeb Alhammadi, Aldasheva Laura

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper examines the development of continuous signal pre-processing methods for segmentation, with a particular emphasis on the application of machine learning. Signal segmentation plays a key role in various fields such as medical diagnostics, image and video processing, and security and surveillance systems. The main focus is on improving the quality of segmentation through data pre-processing, which improves the accuracy and reliability of the final results. As an example, an image segmentation algorithm is presented using the U-Net architecture and the VOC 2012 dataset. The paper also presents a literature review covering current research and development in the field of signal pre-processing and signal segmentation.

Original languageEnglish
Title of host publicationSIST 2025 - 2025 IEEE 5th International Conference on Smart Information Systems and Technologies, Conference Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798331515140
DOIs
Publication statusPublished - 2025
Event5th IEEE International Conference on Smart Information Systems and Technologies, SIST 2025 - Astana, Kazakhstan
Duration: 14 May 202516 May 2025

Publication series

NameSIST 2025 - 2025 IEEE 5th International Conference on Smart Information Systems and Technologies, Conference Proceedings

Conference

Conference5th IEEE International Conference on Smart Information Systems and Technologies, SIST 2025
Country/TerritoryKazakhstan
CityAstana
Period14/05/2516/05/25

Bibliographical note

Publisher Copyright:
© 2025 IEEE.

Keywords

  • image
  • machine learning
  • pre-processing
  • real time
  • video

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