{"id":"https://openalex.org/W4416798263","doi":"https://doi.org/10.1109/tgrs.2025.3638953","title":"Advanced Semi-Supervised Hyperspectral Change Detection via Cross-Temporal Spectral Reconstruction","display_name":"Advanced Semi-Supervised Hyperspectral Change Detection via Cross-Temporal Spectral Reconstruction","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4416798263","doi":"https://doi.org/10.1109/tgrs.2025.3638953"},"language":null,"primary_location":{"id":"doi:10.1109/tgrs.2025.3638953","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3638953","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5087299219","display_name":"Qinsen Liu","orcid":"https://orcid.org/0000-0003-4194-1213"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Qinsen Liu","raw_affiliation_strings":["School of Computer Science and Engineering, Xi&#x2019;an University of Technology, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Xi&#x2019;an University of Technology, Xi&#x2019;an, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070913913","display_name":"Bangyong Sun","orcid":"https://orcid.org/0000-0002-0265-1785"},"institutions":[{"id":"https://openalex.org/I4210131919","display_name":"Xi'an University of Technology","ror":"https://ror.org/038avdt50","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210131919"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bangyong Sun","raw_affiliation_strings":["School of Printing, Packaging and Digital Media, Xi&#x2019;an University of Technology, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"School of Printing, Packaging and Digital Media, Xi&#x2019;an University of Technology, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I4210131919"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5087299219"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.49025654,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"63","issue":null,"first_page":"1","last_page":"15"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9907000064849854,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9907000064849854,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.006099999882280827,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.000699999975040555,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.9291999936103821},{"id":"https://openalex.org/keywords/change-detection","display_name":"Change detection","score":0.574999988079071},{"id":"https://openalex.org/keywords/full-spectral-imaging","display_name":"Full spectral imaging","score":0.5392000079154968},{"id":"https://openalex.org/keywords/spectral-signature","display_name":"Spectral signature","score":0.49779999256134033},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.49470001459121704},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4934999942779541},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.4641999900341034},{"id":"https://openalex.org/keywords/spectral-shape-analysis","display_name":"Spectral shape analysis","score":0.4555000066757202},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.42559999227523804}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9291999936103821},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.574999988079071},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5626000165939331},{"id":"https://openalex.org/C78660771","wikidata":"https://www.wikidata.org/wiki/Q5508206","display_name":"Full spectral imaging","level":3,"score":0.5392000079154968},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5358999967575073},{"id":"https://openalex.org/C176641082","wikidata":"https://www.wikidata.org/wiki/Q2446767","display_name":"Spectral signature","level":2,"score":0.49779999256134033},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.49470001459121704},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4934999942779541},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.4641999900341034},{"id":"https://openalex.org/C152822103","wikidata":"https://www.wikidata.org/wiki/Q7575207","display_name":"Spectral shape analysis","level":3,"score":0.4555000066757202},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44699999690055847},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.42559999227523804},{"id":"https://openalex.org/C114700698","wikidata":"https://www.wikidata.org/wiki/Q2882278","display_name":"Spectral bands","level":2,"score":0.42239999771118164},{"id":"https://openalex.org/C2780648208","wikidata":"https://www.wikidata.org/wiki/Q3001793","display_name":"Land cover","level":3,"score":0.3959999978542328},{"id":"https://openalex.org/C2983668108","wikidata":"https://www.wikidata.org/wiki/Q280453","display_name":"Spectral analysis","level":3,"score":0.3774999976158142},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.374099999666214},{"id":"https://openalex.org/C2776845940","wikidata":"https://www.wikidata.org/wiki/Q3113127","display_name":"Spectral slope","level":3,"score":0.3605000078678131},{"id":"https://openalex.org/C2776836416","wikidata":"https://www.wikidata.org/wiki/Q1364844","display_name":"False alarm","level":2,"score":0.3278000056743622},{"id":"https://openalex.org/C2778740170","wikidata":"https://www.wikidata.org/wiki/Q7575210","display_name":"Spectral space","level":2,"score":0.32739999890327454},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.29989999532699585},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.296099990606308},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.288100004196167},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.28220000863075256},{"id":"https://openalex.org/C2985105764","wikidata":"https://www.wikidata.org/wiki/Q1331626","display_name":"Spectral function","level":2,"score":0.275299996137619},{"id":"https://openalex.org/C3232514","wikidata":"https://www.wikidata.org/wiki/Q7575196","display_name":"Spectral imaging","level":2,"score":0.27480000257492065},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.26010000705718994},{"id":"https://openalex.org/C23463724","wikidata":"https://www.wikidata.org/wiki/Q2308831","display_name":"Spectral method","level":2,"score":0.25609999895095825},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.25209999084472656}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2025.3638953","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3638953","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G287059667","display_name":null,"funder_award_id":"23JY063","funder_id":"https://openalex.org/F4320336746","funder_display_name":"Key Science and Technology Research Project in Jiangxi Province Department of Education"},{"id":"https://openalex.org/G4350466949","display_name":null,"funder_award_id":"62076199","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8335163139","display_name":null,"funder_award_id":"62471386","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"},{"id":"https://openalex.org/F4320336746","display_name":"Key Science and Technology Research Project in Jiangxi Province Department of Education","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W1903029394","https://openalex.org/W1964069486","https://openalex.org/W1977942753","https://openalex.org/W1997413270","https://openalex.org/W1998595580","https://openalex.org/W2001298088","https://openalex.org/W2008265903","https://openalex.org/W2036798369","https://openalex.org/W2161570034","https://openalex.org/W2165577558","https://openalex.org/W2166508941","https://openalex.org/W2741377155","https://openalex.org/W2766046900","https://openalex.org/W2884822772","https://openalex.org/W2900587135","https://openalex.org/W2902788350","https://openalex.org/W2910587630","https://openalex.org/W2954332586","https://openalex.org/W2964257934","https://openalex.org/W3028000844","https://openalex.org/W3151351087","https://openalex.org/W3171427178","https://openalex.org/W3214821343","https://openalex.org/W4211155378","https://openalex.org/W4285177833","https://openalex.org/W4285179070","https://openalex.org/W4293812296","https://openalex.org/W4316013166","https://openalex.org/W4319865968","https://openalex.org/W4319996564","https://openalex.org/W4323064994","https://openalex.org/W4327808525","https://openalex.org/W4384558020","https://openalex.org/W4386918724","https://openalex.org/W4391074589","https://openalex.org/W4392187965","https://openalex.org/W4392543909","https://openalex.org/W4398151431","https://openalex.org/W4401070619","https://openalex.org/W4402508323","https://openalex.org/W4402742852","https://openalex.org/W4403294835","https://openalex.org/W4404371563","https://openalex.org/W4406280531","https://openalex.org/W4406610810","https://openalex.org/W4408029970","https://openalex.org/W4410770559"],"related_works":[],"abstract_inverted_index":{"Hyperspectral":[0],"change":[1,136],"detection":[2],"(HSI-CD)":[3],"serves":[4],"as":[5,43,121],"an":[6,62,144],"advanced":[7],"technique":[8],"for":[9,79],"monitoring":[10],"surface":[11],"changes":[12,123],"by":[13,111],"leveraging":[14],"spectral":[15,23,49,95,106,112,133,183],"differences":[16,24,50,113],"between":[17,25],"multi-temporal":[18,29],"hyperspectral":[19],"images.":[20],"Ideally,":[21],"the":[22,88,104,131,151,168,179,199],"unchanged":[26,52,91,115],"areas":[27,53,92,116],"across":[28],"images":[30],"should":[31],"be":[32,56],"minimal.":[33],"However,":[34],"in":[35,51,68,114,126],"practical":[36],"applications,":[37],"due":[38,117],"to":[39,61,102,118,138,170],"various":[40],"factors":[41,119],"such":[42,120],"imaging":[44],"conditions":[45],"and":[46,124,185,202],"seasonal":[47,122],"variations,":[48],"can":[54,85],"still":[55],"significant,":[57],"which":[58,84,149],"may":[59],"lead":[60],"increased":[63],"likelihood":[64],"of":[65,181,216],"false":[66,187],"alarms":[67],"CD.":[69],"In":[70],"this":[71],"article,":[72],"we":[73,142],"propose":[74,143],"a":[75,164,212],"distinct":[76],"reconstruction-guided":[77],"approach":[78],"semi-supervised":[80,146],"HSI-CD,":[81],"termed":[82],"CSR-Net,":[83],"precisely":[86],"distinguish":[87],"changed":[89],"or":[90],"with":[93,211],"significant":[94],"differences.":[96],"Specifically,":[97],"CSR-Net":[98,201],"encodes":[99],"input":[100],"HSI":[101],"reconstruct":[103],"corrected":[105,182],"sequences,":[107],"mitigating":[108],"errors":[109],"caused":[110],"variations":[125],"land":[127],"cover":[128],"characteristics.":[129],"Subsequently,":[130],"reconstructed":[132],"sequences":[134,184],"undergo":[135],"analysis":[137],"detect":[139],"changes.":[140],"Moreover,":[141],"innovative":[145],"HSI-CD":[147,195],"loss,":[148],"weights":[150],"mean":[152],"squared":[153],"error":[154],"loss":[155,162,203],"based":[156],"on":[157,192],"binary":[158],"CD":[159],"results.":[160],"This":[161],"introduces":[163],"constraint":[165],"that":[166,198],"enables":[167],"model":[169],"learn":[171],"spectral-temporal":[172],"relationships":[173],"from":[174],"unlabeled":[175],"data,":[176],"thereby":[177],"facilitating":[178],"reconstruction":[180],"reducing":[186],"alarms.":[188],"Extensive":[189],"experiments":[190],"conducted":[191],"four":[193],"benchmark":[194],"datasets":[196],"demonstrate":[197],"proposed":[200],"function":[204],"consistently":[205],"outperform":[206],"existing":[207],"state-of-the-art":[208],"methods,":[209],"even":[210],"very":[213],"limited":[214],"number":[215],"labeled":[217],"samples.":[218]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-11-28T00:00:00"}
