{"id":"https://openalex.org/W4396909912","doi":"https://doi.org/10.1109/tgrs.2024.3400966","title":"Single-Stream Extractor Network With Contrastive Pre-Training for Remote-Sensing Change Captioning","display_name":"Single-Stream Extractor Network With Contrastive Pre-Training for Remote-Sensing Change Captioning","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4396909912","doi":"https://doi.org/10.1109/tgrs.2024.3400966"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2024.3400966","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2024.3400966","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/A5030518996","display_name":"Qing Zhou","orcid":"https://orcid.org/0009-0004-3300-0805"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qing Zhou","raw_affiliation_strings":["School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi’an, China","School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi'an, Shaanxi, P. R. China"],"raw_orcid":"https://orcid.org/0009-0004-3300-0805","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi’an, China","institution_ids":["https://openalex.org/I17145004"]},{"raw_affiliation_string":"School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi'an, Shaanxi, P. R. China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001848378","display_name":"Junyu Gao","orcid":"https://orcid.org/0000-0001-6000-8168"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junyu Gao","raw_affiliation_strings":["School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi’an, China","School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi'an, Shaanxi, P. R. China"],"raw_orcid":"https://orcid.org/0000-0001-6000-8168","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi’an, China","institution_ids":["https://openalex.org/I17145004"]},{"raw_affiliation_string":"School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi'an, Shaanxi, P. R. China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032595371","display_name":"Yuan Yuan","orcid":"https://orcid.org/0000-0003-1860-3275"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuan Yuan","raw_affiliation_strings":["School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi’an, China","School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi'an, Shaanxi, P. R. China"],"raw_orcid":"https://orcid.org/0000-0003-1860-3275","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi’an, China","institution_ids":["https://openalex.org/I17145004"]},{"raw_affiliation_string":"School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi'an, Shaanxi, P. R. China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100341321","display_name":"Qi Wang","orcid":"https://orcid.org/0000-0002-7028-4956"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Wang","raw_affiliation_strings":["School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi’an, China","School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi'an, Shaanxi, P. R. China"],"raw_orcid":"https://orcid.org/0000-0002-7028-4956","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi’an, China","institution_ids":["https://openalex.org/I17145004"]},{"raw_affiliation_string":"School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi'an, Shaanxi, P. R. China","institution_ids":["https://openalex.org/I17145004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I17145004"],"apc_list":null,"apc_paid":null,"fwci":5.7525,"has_fulltext":false,"cited_by_count":31,"citation_normalized_percentile":{"value":0.9670505,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"62","issue":null,"first_page":"1","last_page":"14"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9085000157356262,"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":0.9085000157356262,"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/closed-captioning","display_name":"Closed captioning","score":0.8182223439216614},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.726329505443573},{"id":"https://openalex.org/keywords/extractor","display_name":"Extractor","score":0.6748886108398438},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5808715224266052},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.4319716691970825},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3217621147632599},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.1772977113723755},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.08142688870429993}],"concepts":[{"id":"https://openalex.org/C157657479","wikidata":"https://www.wikidata.org/wiki/Q2367247","display_name":"Closed captioning","level":3,"score":0.8182223439216614},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.726329505443573},{"id":"https://openalex.org/C117978034","wikidata":"https://www.wikidata.org/wiki/Q5422192","display_name":"Extractor","level":2,"score":0.6748886108398438},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5808715224266052},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.4319716691970825},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3217621147632599},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.1772977113723755},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.08142688870429993},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C21880701","wikidata":"https://www.wikidata.org/wiki/Q2144042","display_name":"Process engineering","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2024.3400966","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2024.3400966","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":[{"id":"https://metadata.un.org/sdg/4","score":0.6399999856948853,"display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G1058697321","display_name":null,"funder_award_id":"62306241","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1964179093","display_name":null,"funder_award_id":"U21B2041","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":58,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1956340063","https://openalex.org/W1965752813","https://openalex.org/W1979058813","https://openalex.org/W2091511254","https://openalex.org/W2101105183","https://openalex.org/W2108598243","https://openalex.org/W2161599811","https://openalex.org/W2166804859","https://openalex.org/W2194775991","https://openalex.org/W2779054585","https://openalex.org/W2798991696","https://openalex.org/W2842511635","https://openalex.org/W2963084599","https://openalex.org/W2964196083","https://openalex.org/W2986943971","https://openalex.org/W2988981892","https://openalex.org/W3009561768","https://openalex.org/W3027225766","https://openalex.org/W3035524453","https://openalex.org/W3094502228","https://openalex.org/W3100245404","https://openalex.org/W3108170342","https://openalex.org/W3140300848","https://openalex.org/W3144483443","https://openalex.org/W3152083889","https://openalex.org/W3154766321","https://openalex.org/W3175933895","https://openalex.org/W3176330035","https://openalex.org/W3176470992","https://openalex.org/W3180045188","https://openalex.org/W3207627484","https://openalex.org/W4206111836","https://openalex.org/W4211112734","https://openalex.org/W4226359564","https://openalex.org/W4289537913","https://openalex.org/W4289752563","https://openalex.org/W4297808394","https://openalex.org/W4309132693","https://openalex.org/W4310866334","https://openalex.org/W4312745664","https://openalex.org/W4313021481","https://openalex.org/W4377224530","https://openalex.org/W4385245566","https://openalex.org/W4386076603","https://openalex.org/W4386590775","https://openalex.org/W4387350510","https://openalex.org/W4391941753","https://openalex.org/W4391947336","https://openalex.org/W4392399584","https://openalex.org/W6631190155","https://openalex.org/W6678262379","https://openalex.org/W6682631176","https://openalex.org/W6685322675","https://openalex.org/W6774670964","https://openalex.org/W6779997284","https://openalex.org/W6846580343","https://openalex.org/W6855538357"],"related_works":["https://openalex.org/W4210416330","https://openalex.org/W2775506363","https://openalex.org/W3088136942","https://openalex.org/W4290852288","https://openalex.org/W2949362007","https://openalex.org/W4388893791","https://openalex.org/W4283207562","https://openalex.org/W2963177403","https://openalex.org/W2330246314","https://openalex.org/W2949522393"],"abstract_inverted_index":{"Remote":[0],"sensing":[1],"(RS)":[2],"image":[3,112],"change":[4,18],"captioning":[5,19],"is":[6],"a":[7,123,131,161,168],"visual":[8,26,62],"semantic":[9],"understanding":[10],"task":[11],"that":[12],"has":[13],"received":[14],"increasing":[15],"attention.":[16],"The":[17,65,200],"methods":[20,47],"are":[21,205],"required":[22],"to":[23,142,152],"understand":[24],"the":[25,29,33,52,61,95,114,144,177,184,193],"information":[27],"of":[28,130,179,198],"images":[30,83,138],"and":[31,84,99,147,167,182,190,195,202],"capture":[32],"most":[34],"significant":[35],"difference":[36,53,91,157,172,185],"between":[37,77],"them,":[38],"then":[39],"describe":[40],"it":[41],"in":[42,94],"natural":[43,82],"language.":[44],"Most":[45],"existing":[46],"mainly":[48],"focus":[49],"on":[50,79,135],"improving":[51],"feature":[54,63,67,92,154,163],"encoder":[55],"or":[56],"language":[57],"decoder,":[58],"while":[59],"ignoring":[60],"extractor.":[64,116],"current":[66],"extractors":[68],"suffer":[69],"from":[70],"several":[71],"issues,":[72,120],"including":[73],"1)":[74],"domain":[75,145],"gap":[76,146],"pre-training":[78],"single":[80],"temporal":[81,110,180],"downstream":[85],"bi-temporal":[86,136],"RS":[87,137],"task,":[88],"2)":[89],"limited":[90],"modeling":[93,155],"implicit":[96],"single-stream":[97,132],"network,":[98],"3)":[100],"high":[101,148],"computational":[102,149],"costs":[103],"caused":[104],"by":[105],"extracting":[106],"features":[107,181,186],"for":[108,156],"each":[109],"phase":[111],"under":[113],"dual-stream":[115],"To":[117],"address":[118],"these":[119],"we":[121,159],"propose":[122,160],"Single-stream":[124],"Extractor":[125],"Network":[126],"(SEN).":[127],"It":[128],"consists":[129],"extractor":[133],"pre-trained":[134],"using":[139],"contrastive":[140],"learning":[141],"mitigate":[143],"cost.":[150],"Additionally,":[151],"improve":[153],"information,":[158],"shallow":[162],"embedding":[164],"(SFE)":[165],"module":[166],"cross":[169],"attention":[170],"guided":[171],"(CAGD)":[173],"module,":[174],"which":[175],"enhance":[176],"representation":[178],"extract":[183],"explicitly.":[187],"Extensive":[188],"experiments":[189],"visualizations":[191],"demonstrate":[192],"effectiveness":[194],"advanced":[196],"performance":[197],"SEN.":[199],"code":[201],"model":[203],"weights":[204],"available":[206],"at":[207],"https://github.com/mrazhou/SEN.":[208]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":23},{"year":2024,"cited_by_count":3}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}