Unsupervised Cross-Scene Aerial Image Segmentation via Spectral Space Transferring and Pseudo-Label...
Unsupervised Cross-Scene Aerial Image Segmentation via Spectral Space Transferring and Pseudo-Label Revising
About this item
Full title
Author / Creator
Liu, Wenjie , Zhang, Wenkai , Sun, Xian and Guo, Zhi
Publisher
Basel: MDPI AG
Journal title
Language
English
Formats
Publication information
Publisher
Basel: MDPI AG
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More information
Scope and Contents
Contents
Unsupervised domain adaptation (UDA) is essential since manually labeling pixel-level annotations is consuming and expensive. Since the domain discrepancies have not been well solved, existing UDA approaches yield poor performance compared with supervised learning approaches. In this paper, we propose a novel sequential learning network (SLNet) for...
Alternative Titles
Full title
Unsupervised Cross-Scene Aerial Image Segmentation via Spectral Space Transferring and Pseudo-Label Revising
Authors, Artists and Contributors
Author / Creator
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Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_2818edb256c849aa837dd46947b0f2a9
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_2818edb256c849aa837dd46947b0f2a9
Other Identifiers
ISSN
2072-4292
E-ISSN
2072-4292
DOI
10.3390/rs15051207
