Knowledge Transfer-Based Multiple Data Sets Collaborative Analysis for Hyperspectral Band Selection

Jiao Shi, Xi Zhang, Zeping Zhang, Xiaoyang Li, Deyun Zhou, Yu Lei

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

Abstract

The paper presents a knowledge transfer based collaborative analysis method for hyperspectral band selection. This collaborative analysis method establishes different band selection tasks for multiple data sets, cooperatively analyzes the shared spectral spatial structure between hyperspectral data sets, so as to improve the performance of band selection tasks for each data set. The transfer probability is adjusted dynamically to realize spectral knowledge transfer effectively and improve the cooperation ability of collaborative analysis. Experiments indicate that the proposed collaborative analysis method works more efficiently than the comparison methods.

Original languageEnglish
Title of host publicationProceedings of 2021 7th IEEE International Conference on Cloud Computing and Intelligence Systems, CCIS 2021
EditorsDeyi Li, Mengqi Zhou, Weining Wang, Yaru Zou, Meng Luo, Qian Zhang
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages94-98
Number of pages5
ISBN (Electronic)9781665441490
DOIs
StatePublished - 2021
Event7th IEEE International Conference on Cloud Computing and Intelligence Systems, CCIS 2021 - Xi'an, China
Duration: 7 Nov 20218 Nov 2021

Publication series

NameProceedings of 2021 7th IEEE International Conference on Cloud Computing and Intelligence Systems, CCIS 2021

Conference

Conference7th IEEE International Conference on Cloud Computing and Intelligence Systems, CCIS 2021
Country/TerritoryChina
CityXi'an
Period7/11/218/11/21

Keywords

  • Band selection
  • Collaborative analysis
  • Evolutionary multitasking optimization
  • Hyperspectral images
  • Knowledge transfer

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