{"id":"https://openalex.org/W4285157526","doi":"https://doi.org/10.1109/tgrs.2022.3184080","title":"Few-Shot Scene Classification of Optical Remote Sensing Images Leveraging Calibrated Pretext Tasks","display_name":"Few-Shot Scene Classification of Optical Remote Sensing Images Leveraging Calibrated Pretext Tasks","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4285157526","doi":"https://doi.org/10.1109/tgrs.2022.3184080"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2022.3184080","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2022.3184080","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/A5004950171","display_name":"Hong Ji","orcid":"https://orcid.org/0000-0003-0812-4334"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hong Ji","raw_affiliation_strings":["School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084683976","display_name":"Zhi Gao","orcid":"https://orcid.org/0000-0003-3325-1183"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhi Gao","raw_affiliation_strings":["School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108625236","display_name":"Yongjun Zhang","orcid":"https://orcid.org/0000-0001-9845-4251"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongjun Zhang","raw_affiliation_strings":["School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031253591","display_name":"Yu Wan","orcid":"https://orcid.org/0000-0003-1649-9611"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Wan","raw_affiliation_strings":["School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028044534","display_name":"Can Li","orcid":"https://orcid.org/0000-0002-6850-5721"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Can Li","raw_affiliation_strings":["School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022219449","display_name":"Tiancan Mei","orcid":"https://orcid.org/0000-0003-4166-7891"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tiancan Mei","raw_affiliation_strings":["School of Electronic Information, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic Information, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5004950171"],"corresponding_institution_ids":["https://openalex.org/I37461747"],"apc_list":null,"apc_paid":null,"fwci":4.5091,"has_fulltext":false,"cited_by_count":35,"citation_normalized_percentile":{"value":0.9522234,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"60","issue":null,"first_page":"1","last_page":"13"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9977999925613403,"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"}},"topics":[{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9977999925613403,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9976999759674072,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9388999938964844,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/computer-science","display_name":"Computer science","score":0.8527684211730957},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.6334140300750732},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.581841230392456},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5089619159698486},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.13654503226280212}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8527684211730957},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.6334140300750732},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.581841230392456},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5089619159698486},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.13654503226280212}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2022.3184080","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2022.3184080","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":[{"score":0.41999998688697815,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G2131151903","display_name":null,"funder_award_id":"42192580","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3336318780","display_name":null,"funder_award_id":"2020CFA003","funder_id":"https://openalex.org/F4320322186","funder_display_name":"Natural Science Foundation of Hubei Province"},{"id":"https://openalex.org/G4105891685","display_name":null,"funder_award_id":"2021AAA010-3","funder_id":"https://openalex.org/F4320329860","funder_display_name":"National Science and Technology Major Project"},{"id":"https://openalex.org/G4308293926","display_name":null,"funder_award_id":"42192583","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5149724285","display_name":null,"funder_award_id":"2021CFA088","funder_id":"https://openalex.org/F4320322186","funder_display_name":"Natural Science Foundation of Hubei Province"},{"id":"https://openalex.org/G5431101322","display_name":null,"funder_award_id":"2021AAA010","funder_id":"https://openalex.org/F4320329860","funder_display_name":"National Science and Technology Major Project"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322186","display_name":"Natural Science Foundation of Hubei Province","ror":null},{"id":"https://openalex.org/F4320329860","display_name":"National Science and Technology Major Project","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":70,"referenced_works":["https://openalex.org/W219040644","https://openalex.org/W2020912318","https://openalex.org/W2064675550","https://openalex.org/W2156909104","https://openalex.org/W2187089797","https://openalex.org/W2194775991","https://openalex.org/W2294802479","https://openalex.org/W2321533354","https://openalex.org/W2326925005","https://openalex.org/W2515866431","https://openalex.org/W2592962403","https://openalex.org/W2609468337","https://openalex.org/W2742093937","https://openalex.org/W2752788177","https://openalex.org/W2790898247","https://openalex.org/W2898204262","https://openalex.org/W2912811302","https://openalex.org/W2921700058","https://openalex.org/W2941333398","https://openalex.org/W2944029760","https://openalex.org/W2963943197","https://openalex.org/W2964105864","https://openalex.org/W2965949912","https://openalex.org/W2969666521","https://openalex.org/W2981952041","https://openalex.org/W2994633389","https://openalex.org/W3007041883","https://openalex.org/W3009081299","https://openalex.org/W3023371261","https://openalex.org/W3032752459","https://openalex.org/W3036045183","https://openalex.org/W3088971399","https://openalex.org/W3096675569","https://openalex.org/W3096727283","https://openalex.org/W3100156920","https://openalex.org/W3104355817","https://openalex.org/W3105577662","https://openalex.org/W3108655343","https://openalex.org/W3121583704","https://openalex.org/W3124294118","https://openalex.org/W3125493368","https://openalex.org/W3131740536","https://openalex.org/W3166792421","https://openalex.org/W3174159092","https://openalex.org/W3177423475","https://openalex.org/W3188824417","https://openalex.org/W3199708111","https://openalex.org/W3200370304","https://openalex.org/W3203918617","https://openalex.org/W3205249428","https://openalex.org/W4254952533","https://openalex.org/W4294646197","https://openalex.org/W6717697761","https://openalex.org/W6735236233","https://openalex.org/W6736057607","https://openalex.org/W6742288159","https://openalex.org/W6743661861","https://openalex.org/W6747899497","https://openalex.org/W6750254146","https://openalex.org/W6751281049","https://openalex.org/W6753311412","https://openalex.org/W6754484989","https://openalex.org/W6758126075","https://openalex.org/W6760184523","https://openalex.org/W6765696844","https://openalex.org/W6774314701","https://openalex.org/W6776700526","https://openalex.org/W6779702771","https://openalex.org/W6789128979","https://openalex.org/W6796864494"],"related_works":["https://openalex.org/W2989932438","https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W2186333919","https://openalex.org/W4387297750","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3209574120"],"abstract_inverted_index":{"Small":[0],"data":[1,12],"holds":[2],"big":[3],"AI":[4,13],"potential.":[5],"As":[6],"one":[7],"of":[8,55,97,104],"the":[9,18,85,94,102,114,120,149,162,169],"promising":[10],"small":[11],"approaches,":[14],"few-shot":[15,52],"learning":[16,103,109],"has":[17],"goal":[19],"to":[20,39,80,92,100,111,123,160,167],"learn":[21],"a":[22,63,72,154],"model":[23,65,158],"efficiently":[24],"that":[25,66,185,194],"can":[26],"recognize":[27,93],"novel":[28],"classes":[29,70],"with":[30],"extremely":[31],"limited":[32],"training":[33],"samples.":[34],"Therefore":[35],"it":[36],"is":[37],"critical":[38],"accumulate":[40],"useful":[41],"prior":[42],"knowledge":[43],"obtained":[44],"from":[45,62],"large-scale":[46],"base":[47,69],"class":[48,139],"dataset.":[49],"To":[50,146],"realize":[51],"scene":[53],"classification":[54],"optical":[56],"remote":[57,176],"sensing":[58,177],"images,":[59],"we":[60,152],"start":[61],"baseline":[64],"trains":[67],"all":[68],"using":[71],"standard":[73],"cross-entropy":[74],"loss":[75],"leveraging":[76],"two":[77,134],"auxiliary":[78],"objectives":[79],"capture":[81],"intrinsical":[82],"characteristics":[83],"across":[84],"semantic":[86,138],"classes.":[87],"Specifically,":[88],"rotation":[89,96],"prediction":[90,140],"learns":[91],"2D":[95],"an":[98,143],"input":[99],"guide":[101],"class-transferable":[105],"knowledge,":[106],"and":[107,127,137,182,190],"contrastive":[108],"aims":[110],"pull":[112],"together":[113],"positive":[115],"pairs":[116,122],"while":[117],"pushing":[118],"apart":[119],"negative":[121],"promote":[124],"intra-class":[125],"consistency":[126],"inter-class":[128],"inconsistency.":[129],"We":[130],"jointly":[131],"optimize":[132],"such":[133],"pretext":[135,163],"tasks":[136,164],"task":[141],"in":[142],"end-to-end":[144],"manner.":[145],"further":[147],"overcome":[148],"overfitting":[150],"issue,":[151],"introduce":[153],"regularization":[155],"technique,":[156],"adversarial":[157],"perturbation,":[159],"calibrate":[161],"so":[165],"as":[166],"enhance":[168],"generalization":[170],"ability.":[171],"Extensive":[172],"experiments":[173],"on":[174],"public":[175],"benchmarks":[178],"including":[179],"NWPU-RESISC45,":[180],"AID,":[181],"WHU-RS-19":[183],"demonstrate":[184],"our":[186],"method":[187],"works":[188],"effectively":[189],"achieves":[191],"best":[192],"performance":[193],"significantly":[195],"outperforms":[196],"many":[197],"state-of-the-art":[198],"approaches.":[199]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":1}],"updated_date":"2026-02-25T08:12:03.925757","created_date":"2025-10-10T00:00:00"}
