{"id":"https://openalex.org/W4224933328","doi":"https://doi.org/10.1109/icassp43922.2022.9746248","title":"A Two-Stage Contrastive Learning Framework For Imbalanced Aerial Scene Recognition","display_name":"A Two-Stage Contrastive Learning Framework For Imbalanced Aerial Scene Recognition","publication_year":2022,"publication_date":"2022-04-27","ids":{"openalex":"https://openalex.org/W4224933328","doi":"https://doi.org/10.1109/icassp43922.2022.9746248"},"language":"en","primary_location":{"id":"doi:10.1109/icassp43922.2022.9746248","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp43922.2022.9746248","pdf_url":null,"source":{"id":"https://openalex.org/S4363607702","display_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-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/A5038473009","display_name":"Lexing Huang","orcid":"https://orcid.org/0009-0009-0262-2325"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lexing Huang","raw_affiliation_strings":["Xiamen University,School of Informatics,China","School of Informatics, Xiamen University, China"],"affiliations":[{"raw_affiliation_string":"Xiamen University,School of Informatics,China","institution_ids":["https://openalex.org/I191208505"]},{"raw_affiliation_string":"School of Informatics, Xiamen University, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049595858","display_name":"Senlin Cai","orcid":"https://orcid.org/0009-0007-2345-635X"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Senlin Cai","raw_affiliation_strings":["Xiamen University,School of Informatics,China","School of Informatics, Xiamen University, China"],"affiliations":[{"raw_affiliation_string":"Xiamen University,School of Informatics,China","institution_ids":["https://openalex.org/I191208505"]},{"raw_affiliation_string":"School of Informatics, Xiamen University, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052754372","display_name":"Yihong Zhuang","orcid":"https://orcid.org/0000-0002-3176-3217"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yihong Zhuang","raw_affiliation_strings":["Xiamen University,School of Informatics,China","School of Informatics, Xiamen University, China"],"affiliations":[{"raw_affiliation_string":"Xiamen University,School of Informatics,China","institution_ids":["https://openalex.org/I191208505"]},{"raw_affiliation_string":"School of Informatics, Xiamen University, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030586470","display_name":"Changxing Jing","orcid":"https://orcid.org/0000-0002-7866-7476"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changxing Jing","raw_affiliation_strings":["Xiamen University,School of Informatics,China","School of Informatics, Xiamen University, China"],"affiliations":[{"raw_affiliation_string":"Xiamen University,School of Informatics,China","institution_ids":["https://openalex.org/I191208505"]},{"raw_affiliation_string":"School of Informatics, Xiamen University, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100772804","display_name":"Yue Huang","orcid":"https://orcid.org/0000-0002-3913-9400"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yue Huang","raw_affiliation_strings":["Xiamen University,School of Informatics,China","School of Informatics, Xiamen University, China"],"affiliations":[{"raw_affiliation_string":"Xiamen University,School of Informatics,China","institution_ids":["https://openalex.org/I191208505"]},{"raw_affiliation_string":"School of Informatics, Xiamen University, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068316504","display_name":"Xiaotong Tu","orcid":"https://orcid.org/0000-0002-7190-2429"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaotong Tu","raw_affiliation_strings":["Xiamen University,School of Informatics,China","School of Informatics, Xiamen University, China"],"affiliations":[{"raw_affiliation_string":"Xiamen University,School of Informatics,China","institution_ids":["https://openalex.org/I191208505"]},{"raw_affiliation_string":"School of Informatics, Xiamen University, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052820597","display_name":"Xinghao Ding","orcid":"https://orcid.org/0000-0003-2288-5287"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinghao Ding","raw_affiliation_strings":["Xiamen University,School of Informatics,China","School of Informatics, Xiamen University, China"],"affiliations":[{"raw_affiliation_string":"Xiamen University,School of Informatics,China","institution_ids":["https://openalex.org/I191208505"]},{"raw_affiliation_string":"School of Informatics, Xiamen University, China","institution_ids":["https://openalex.org/I191208505"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5038473009"],"corresponding_institution_ids":["https://openalex.org/I191208505"],"apc_list":null,"apc_paid":null,"fwci":0.5194,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.6127451,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"25","issue":null,"first_page":"3518","last_page":"3522"},"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":0.9932000041007996,"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":0.9932000041007996,"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/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9882000088691711,"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/T11438","display_name":"Retinal Imaging and Analysis","score":0.983299970626831,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7590473294258118},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7534019947052002},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6638110876083374},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.6502801179885864},{"id":"https://openalex.org/keywords/aerial-image","display_name":"Aerial image","score":0.5891599059104919},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.48094671964645386},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.463478147983551},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4619264006614685},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4266113042831421},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.19894620776176453}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7590473294258118},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7534019947052002},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6638110876083374},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.6502801179885864},{"id":"https://openalex.org/C2776429412","wikidata":"https://www.wikidata.org/wiki/Q4688011","display_name":"Aerial image","level":3,"score":0.5891599059104919},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48094671964645386},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.463478147983551},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4619264006614685},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4266113042831421},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.19894620776176453}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp43922.2022.9746248","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp43922.2022.9746248","pdf_url":null,"source":{"id":"https://openalex.org/S4363607702","display_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W114517082","https://openalex.org/W1709548961","https://openalex.org/W1941659294","https://openalex.org/W2097117768","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2339172597","https://openalex.org/W2440599146","https://openalex.org/W2515866431","https://openalex.org/W2592962403","https://openalex.org/W2783397226","https://openalex.org/W2804532080","https://openalex.org/W2963263347","https://openalex.org/W2964137095","https://openalex.org/W2976281527","https://openalex.org/W2989678931","https://openalex.org/W2995197345","https://openalex.org/W3005680577","https://openalex.org/W3016055451","https://openalex.org/W3034601242","https://openalex.org/W3048631361","https://openalex.org/W3102692100","https://openalex.org/W3105577662","https://openalex.org/W4287812705","https://openalex.org/W6637616945","https://openalex.org/W6684191040","https://openalex.org/W6726497184","https://openalex.org/W6768920361","https://openalex.org/W6768943855","https://openalex.org/W6770886966","https://openalex.org/W6774314701","https://openalex.org/W6776700526"],"related_works":["https://openalex.org/W2125652721","https://openalex.org/W1540371141","https://openalex.org/W4231274751","https://openalex.org/W2154063878","https://openalex.org/W2556012038","https://openalex.org/W2005234362","https://openalex.org/W2162970382","https://openalex.org/W1997235926","https://openalex.org/W3147207884","https://openalex.org/W1836423264"],"abstract_inverted_index":{"In":[0,37,107],"real-world":[1],"scenarios,":[2],"aerial":[3,34,61,88,101,139,155],"image":[4,140],"datasets":[5,29,141],"are":[6],"generally":[7],"class":[8,27],"imbalanced,":[9],"where":[10],"the":[11,18,66,78,85,98,104,108,114,122,137,143,146,153],"majority":[12],"classes":[13,20],"have":[14,22],"rich":[15],"samples,":[16],"while":[17],"minority":[19],"only":[21],"a":[23,42,72,127],"few":[24],"samples.":[25],"Such":[26],"imbalanced":[28,138,154],"bring":[30],"great":[31],"challenges":[32],"to":[33,50,76,84,96,116,125],"scene":[35,62,156],"recognition.":[36,63,157],"this":[38],"paper,":[39],"we":[40,70,91,112],"explore":[41],"novel":[43],"two-stage":[44,148],"contrastive":[45,81,94,149],"learning":[46,55,68,82,95,110,150],"framework,":[47],"which":[48],"aims":[49],"take":[51],"care":[52],"of":[53,80,87,103,133,145],"representation":[54,67,119],"and":[56,120],"classifier":[57],"learning,":[58],"thereby":[59],"boosting":[60],"Specifically,":[64],"in":[65],"stage,":[69,111],"design":[71],"data":[73],"augmentation":[74],"policy":[75],"improve":[77],"potential":[79],"according":[83],"characteristics":[86],"images.":[89],"And":[90],"employ":[92],"supervised":[93],"learn":[97],"association":[99],"between":[100],"images":[102],"same":[105],"scene.":[106],"classification":[109],"fix":[113],"encoder":[115],"maintain":[117],"good":[118],"use":[121],"re-balancing":[123],"strategy":[124],"train":[126],"less":[128],"biased":[129],"classifier.":[130],"A":[131],"variety":[132],"experimental":[134],"results":[135],"on":[136],"show":[142],"advantages":[144],"proposed":[147],"framework":[151],"for":[152]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}