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However, remote sensing images obtained from the same satellite sensor often show a data distribution drift problem due to the different cloud shapes and land-cover types on the Earth\u2019s surface. Therefore, there are domain distribution gaps between labeled and unlabeled satellite images. To solve this problem, we take the domain shift problem into account for the semi-supervised learning (SSL) network. Feature-level and output-level domain adaptations are applied to reduce the domain distribution gaps between labeled and unlabeled images, thus improving predicted results accuracy of the SSL network. Experimental results on Landsat-8 OLI and GF-1 WFV multispectral images demonstrate that the proposed semi-supervised cloud detection network (SSCDnet) is able to achieve promising cloud detection performance when using a limited number of labeled samples and outperforms several state-of-the-art SSL methods.<\/jats:p>","DOI":"10.3390\/rs14112641","type":"journal-article","created":{"date-parts":[[2022,6,1]],"date-time":"2022-06-01T21:43:42Z","timestamp":1654119822000},"page":"2641","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Semi-Supervised Cloud Detection in Satellite Images by Considering the Domain Shift Problem"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3361-5135","authenticated-orcid":false,"given":"Jianhua","family":"Guo","sequence":"first","affiliation":[{"name":"Department of Aerospace and Geodesy, Data Science in Earth Observation, Technical University of Munich (TUM), 80333 Munich, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0906-7290","authenticated-orcid":false,"given":"Qingsong","family":"Xu","sequence":"additional","affiliation":[{"name":"Department of Aerospace and Geodesy, Data Science in Earth Observation, Technical University of Munich (TUM), 80333 Munich, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yue","family":"Zeng","sequence":"additional","affiliation":[{"name":"Department of Aerospace and Geodesy, Data Science in Earth Observation, Technical University of Munich (TUM), 80333 Munich, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2794-3557","authenticated-orcid":false,"given":"Zhiheng","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Aerospace Science and Technology, Xidian University, Xi\u2019an 710126, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5530-3613","authenticated-orcid":false,"given":"Xiaoxiang","family":"Zhu","sequence":"additional","affiliation":[{"name":"Department of Aerospace and Geodesy, Data Science in Earth Observation, Technical University of Munich (TUM), 80333 Munich, Germany"},{"name":"Remote Sensing Technology Institute, German Aerospace Center (DLR), 82234 We\u00dfling, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,5,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1007\/s12145-017-0286-6","article-title":"An overview of satellite remote sensing technology used in China\u2019s environmental protection","volume":"10","author":"Zhao","year":"2017","journal-title":"Earth Sci. 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