{"id":"https://openalex.org/W7125901099","doi":"https://doi.org/10.1109/jstars.2026.3658638","title":"Self-Supervised Contrastive Learning for Hyperspectral Anomaly Detection With Block-Pseudolabel Masked Data Augmentation","display_name":"Self-Supervised Contrastive Learning for Hyperspectral Anomaly Detection With Block-Pseudolabel Masked Data Augmentation","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7125901099","doi":"https://doi.org/10.1109/jstars.2026.3658638"},"language":"en","primary_location":{"id":"doi:10.1109/jstars.2026.3658638","doi":"https://doi.org/10.1109/jstars.2026.3658638","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2026.3658638","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-scientific","cwts-core","doaj","dongbi-d","jufo-1","norway-1","oarl","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/jstars.2026.3658638","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101405735","display_name":"Meiping Song","orcid":"https://orcid.org/0000-0002-4489-5470","observed_orcids":["https://orcid.org/0000-0002-4489-5470"]},"institutions":[{"id":"https://openalex.org/I2800517447","display_name":"Guangzhou Academy of Fine Arts","ror":"https://ror.org/044my7157","country_code":"CN","type":"education","lineage":["https://openalex.org/I2800517447"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meiping Song","raw_affiliation_strings":["School of Innovation Design, Guangzhou Academy of Fine Arts, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-4489-5470","affiliations":[{"raw_affiliation_string":"School of Innovation Design, Guangzhou Academy of Fine Arts, Guangzhou, China","institution_ids":["https://openalex.org/I2800517447"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124053043","display_name":"Zhiyuan Jing","orcid":"https://orcid.org/0009-0000-3199-7868","observed_orcids":["https://orcid.org/0009-0000-3199-7868"]},"institutions":[{"id":"https://openalex.org/I43313876","display_name":"Dalian Maritime University","ror":"https://ror.org/002b7nr53","country_code":"CN","type":"education","lineage":["https://openalex.org/I43313876"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiyuan Jing","raw_affiliation_strings":["Information and Technology College, Dalian Maritime University, Dalian, China"],"raw_orcid":"https://orcid.org/0009-0000-3199-7868","affiliations":[{"raw_affiliation_string":"Information and Technology College, Dalian Maritime University, Dalian, China","institution_ids":["https://openalex.org/I43313876"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135853285","display_name":"Xudong Sun","orcid":"https://orcid.org/0009-0002-1211-6425","observed_orcids":["https://orcid.org/0009-0002-1211-6425"]},"institutions":[{"id":"https://openalex.org/I43313876","display_name":"Dalian Maritime University","ror":"https://ror.org/002b7nr53","country_code":"CN","type":"education","lineage":["https://openalex.org/I43313876"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xudong Sun","raw_affiliation_strings":["Information and Technology College, Dalian Maritime University, Dalian, China"],"raw_orcid":"https://orcid.org/0009-0002-1211-6425","affiliations":[{"raw_affiliation_string":"Information and Technology College, Dalian Maritime University, Dalian, China","institution_ids":["https://openalex.org/I43313876"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005467310","display_name":"Yisha Liu","orcid":"https://orcid.org/0000-0003-2083-8612","observed_orcids":["https://orcid.org/0000-0003-2083-8612"]},"institutions":[{"id":"https://openalex.org/I43313876","display_name":"Dalian Maritime University","ror":"https://ror.org/002b7nr53","country_code":"CN","type":"education","lineage":["https://openalex.org/I43313876"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yisha Liu","raw_affiliation_strings":["Information and Technology College, Dalian Maritime University, Dalian, China"],"raw_orcid":"https://orcid.org/0000-0003-2083-8612","affiliations":[{"raw_affiliation_string":"Information and Technology College, Dalian Maritime University, Dalian, China","institution_ids":["https://openalex.org/I43313876"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045675147","display_name":"Haimo Bao","orcid":"https://orcid.org/0000-0001-5706-2155","observed_orcids":["https://orcid.org/0000-0001-5706-2155"]},"institutions":[{"id":"https://openalex.org/I2800517447","display_name":"Guangzhou Academy of Fine Arts","ror":"https://ror.org/044my7157","country_code":"CN","type":"education","lineage":["https://openalex.org/I2800517447"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haimo Bao","raw_affiliation_strings":["School of Innovation Design, Guangzhou Academy of Fine Arts, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-5706-2155","affiliations":[{"raw_affiliation_string":"School of Innovation Design, Guangzhou Academy of Fine Arts, Guangzhou, China","institution_ids":["https://openalex.org/I2800517447"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5121103778","display_name":"Chunyan Yu","orcid":"https://orcid.org/0000-0002-9260-6629","observed_orcids":["https://orcid.org/0000-0002-9260-6629"]},"institutions":[{"id":"https://openalex.org/I43313876","display_name":"Dalian Maritime University","ror":"https://ror.org/002b7nr53","country_code":"CN","type":"education","lineage":["https://openalex.org/I43313876"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunyan Yu","raw_affiliation_strings":["Information and Technology College, Dalian Maritime University, Dalian, China"],"raw_orcid":"https://orcid.org/0000-0002-9260-6629","affiliations":[{"raw_affiliation_string":"Information and Technology College, Dalian Maritime University, Dalian, China","institution_ids":["https://openalex.org/I43313876"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1800,"currency":"USD","value_usd":1800},"apc_paid":{"value":1800,"currency":"USD","value_usd":1800},"fwci":1.9684,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.81889301,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":92,"max":95},"biblio":{"volume":"19","issue":null,"first_page":"6716","last_page":"6727"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.00039999998989515007,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12389","display_name":"Infrared Target Detection Methodologies","score":0.00019999999494757503,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-anomaly-detection","display_name":"hyperspectral anomaly detection","score":0.9990000128746033},{"id":"https://openalex.org/keywords/self-supervised-contrastive-learning","display_name":"self-supervised contrastive learning","score":0.9679999947547913},{"id":"https://openalex.org/keywords/pseudo-labeling","display_name":"pseudo-labeling","score":0.8429999947547913},{"id":"https://openalex.org/keywords/patch-based-classification","display_name":"patch-based classification","score":0.746999979019165},{"id":"https://openalex.org/keywords/anomaly-localization","display_name":"anomaly localization","score":0.8289999961853027},{"id":"https://openalex.org/keywords/false-alarm-reduction","display_name":"false alarm reduction","score":0.6679999828338623}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8827000260353088},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.8149999976158142},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7817000150680542},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7260000109672546},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.6348999738693237},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6093999743461609},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.49549999833106995},{"id":"https://openalex.org/C77052588","wikidata":"https://www.wikidata.org/wiki/Q644307","display_name":"Constant false alarm rate","level":2,"score":0.4767000079154968},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.41499999165534973},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.41370001435279846},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4025000035762787},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.3946000039577484},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.35659998655319214},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3361999988555908},{"id":"https://openalex.org/C2776836416","wikidata":"https://www.wikidata.org/wiki/Q1364844","display_name":"False alarm","level":2,"score":0.32030001282691956},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.31850001215934753},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.30399999022483826},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.27810001373291016},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.26489999890327454},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.2603999972343445}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jstars.2026.3658638","doi":"https://doi.org/10.1109/jstars.2026.3658638","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2026.3658638","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-scientific","cwts-core","doaj","dongbi-d","jufo-1","norway-1","oarl","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1109/jstars.2026.3658638","doi":"https://doi.org/10.1109/jstars.2026.3658638","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2026.3658638","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-scientific","cwts-core","doaj","dongbi-d","jufo-1","norway-1","oarl","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G3283595097","display_name":null,"funder_award_id":"62471079","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5800071179","display_name":"\u57fa\u4e8e\u6d4b\u5ea6\u4fdd\u6301\u548c\u4efb\u52a1\u9a71\u52a8\u7684\u975e\u76d1\u7763\u6ce2\u6bb5\u9009\u62e9\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61971082","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8794430264","display_name":null,"funder_award_id":"62473070","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1981536098","https://openalex.org/W2004491663","https://openalex.org/W2040078680","https://openalex.org/W2047870694","https://openalex.org/W2067897118","https://openalex.org/W2089587382","https://openalex.org/W2124463804","https://openalex.org/W2163129097","https://openalex.org/W2167708128","https://openalex.org/W2183325870","https://openalex.org/W2295576075","https://openalex.org/W2497075055","https://openalex.org/W2592141703","https://openalex.org/W2740976805","https://openalex.org/W2750586932","https://openalex.org/W2782517596","https://openalex.org/W2902857081","https://openalex.org/W2951039757","https://openalex.org/W3005109735","https://openalex.org/W3008839601","https://openalex.org/W3096751897","https://openalex.org/W3122722892","https://openalex.org/W3123098349","https://openalex.org/W3123291413","https://openalex.org/W3130063696","https://openalex.org/W3137199127","https://openalex.org/W3186256209","https://openalex.org/W3196267160","https://openalex.org/W4200080982","https://openalex.org/W4296210064","https://openalex.org/W4318707911","https://openalex.org/W4321380750","https://openalex.org/W4366678167","https://openalex.org/W4389104899","https://openalex.org/W4390873265","https://openalex.org/W4395017619","https://openalex.org/W4401358048","https://openalex.org/W4402350580","https://openalex.org/W4403827055"],"related_works":["https://openalex.org/W4406857995","https://openalex.org/W7139938630","https://openalex.org/W4407566400","https://openalex.org/W4390187403","https://openalex.org/W7134829118","https://openalex.org/W7127900630","https://openalex.org/W4321380750","https://openalex.org/W7139135353","https://openalex.org/W4407952576","https://openalex.org/W4410741538"],"abstract_inverted_index":{"Hyperspectral":[0],"anomaly":[1,43,66,151],"detection":[2,67,127,144,173],"(HAD)":[3],"aims":[4],"to":[5,23,94,114,125,147],"identify":[6],"targets":[7],"deviating":[8],"from":[9],"normal":[10],"patterns":[11],"of":[12,17,134],"background.":[13],"However,":[14],"the":[15,24,80,100,143,150,157],"lack":[16],"labeled":[18],"samples":[19],"pose":[20],"significant":[21],"challenges":[22],"task.":[25],"Self-supervised":[26],"deep":[27],"learning":[28,101],"methods":[29],"have":[30],"shown":[31],"promising":[32],"results":[33,154],"in":[34,123],"this":[35,60],"scenario,":[36],"but":[37],"they":[38],"often":[39],"fall":[40],"into":[41,85,142],"partial":[42],"representations,":[44],"causing":[45],"high":[46,131],"false":[47],"alarm":[48],"rates.":[49],"Effectively":[50],"leveraging":[51],"task":[52],"knowledge":[53,98],"has":[54],"become":[55],"a":[56,64,116],"key":[57],"point.":[58],"In":[59],"paper,":[61],"we":[62],"propose":[63],"hyperspectral":[65,81,165],"method":[68,159],"based":[69],"on":[70,163],"blind-block":[71],"masked":[72],"data":[73,82,92],"augmentation":[74,93],"and":[75,91,109,171],"self-supervised":[76],"contrastive":[77,121],"learning.":[78],"First,":[79],"is":[83,140],"divided":[84],"patches,":[86],"followed":[87],"by":[88],"patch":[89,104],"classification":[90],"generate":[95],"accurate":[96],"prior":[97],"for":[99],"model.":[102],"Second,":[103],"pairs":[105],"with":[106],"their":[107],"pseudo-label":[108,139],"corresponding":[110],"masks":[111],"are":[112],"used":[113],"train":[115],"lightweight":[117],"residual":[118],"network":[119],"integrating":[120],"learning,":[122],"order":[124],"improve":[126],"accuracy":[128],"while":[129],"avoiding":[130],"computational":[132],"cost":[133],"pixel-":[135],"wise":[136],"reconstruction.":[137],"Finally,":[138],"introduced":[141],"process":[145],"again":[146],"further":[148],"guide":[149],"localization.":[152],"Experimental":[153],"show":[155],"that":[156],"proposed":[158],"achieves":[160],"outstanding":[161],"performance":[162],"various":[164],"datasets,":[166],"demonstrating":[167],"strong":[168],"background-anomaly":[169],"separability":[170],"superior":[172],"accuracy.":[174]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-11-01T11:40:01.658920","created_date":"2026-01-29T00:00:00"}