{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T16:25:36Z","timestamp":1774023936108,"version":"3.50.1"},"reference-count":48,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2021,11,3]],"date-time":"2021-11-03T00:00:00Z","timestamp":1635897600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["No.2017YFB1301104 and 2017YFB1001900"],"award-info":[{"award-number":["No.2017YFB1301104 and 2017YFB1001900"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["No.91648204 and 61803375"],"award-info":[{"award-number":["No.91648204 and 61803375"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Hyperspectral image (HSI) clustering is a major challenge due to the redundant spectral information in HSIs. In this paper, we propose a novel deep subspace clustering method that extracts spatial\u2013spectral features via contrastive learning. First, we construct positive and negative sample pairs through data augmentation. Then, the data pairs are projected into feature space using a CNN model. Contrastive learning is conducted by minimizing the distances of positive pairs and maximizing those of negative pairs. Finally, based on their features, spectral clustering is employed to obtain the final result. Experimental results gained over three HSI datasets demonstrate that our proposed method is superior to other state-of-the-art methods.<\/jats:p>","DOI":"10.3390\/rs13214418","type":"journal-article","created":{"date-parts":[[2021,11,3]],"date-time":"2021-11-03T21:57:49Z","timestamp":1635976669000},"page":"4418","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":39,"title":["Deep Spatial-Spectral Subspace Clustering for Hyperspectral Images Based on Contrastive Learning"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1798-8508","authenticated-orcid":false,"given":"Xiang","family":"Hu","sequence":"first","affiliation":[{"name":"The State Key Laboratory of High-Performance Computing, College of Computer, National University of Defense Technology, Changsha 410073, China"}]},{"given":"Teng","family":"Li","sequence":"additional","affiliation":[{"name":"Beijing Institute for Advanced Study, National University of Defense Technology, Beijing 100020, China"},{"name":"College of Advanced Interdisciplinary Studies, National University of Defense Technology, Changsha 410073, China"}]},{"given":"Tong","family":"Zhou","sequence":"additional","affiliation":[{"name":"The State Key Laboratory of High-Performance Computing, College of Computer, National University of Defense Technology, Changsha 410073, China"},{"name":"Beijing Institute for Advanced Study, National University of Defense Technology, Beijing 100020, China"}]},{"given":"Yuanxi","family":"Peng","sequence":"additional","affiliation":[{"name":"The State Key Laboratory of High-Performance Computing, College of Computer, National University of Defense Technology, Changsha 410073, China"}]}],"member":"1968","published-online":{"date-parts":[[2021,11,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"3966","DOI":"10.3390\/rs70403966","article-title":"Global and local real-time anomaly detectors for hyperspectral remote sensing imagery","volume":"7","author":"Zhao","year":"2015","journal-title":"Remote Sens."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"725","DOI":"10.14358\/PERS.80.8.725","article-title":"Improved capability in stone pine forest mapping and management in Lebanon using hyperspectral CHRIS-Proba data relative to Landsat ETM+","volume":"80","author":"Awad","year":"2014","journal-title":"Photogramm. 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