{"id":"https://openalex.org/W4392543853","doi":"https://doi.org/10.1109/tgrs.2024.3373442","title":"SPGC: Shape-Prior-Based Generated Content Data Augmentation for Remote Sensing Object Detection","display_name":"SPGC: Shape-Prior-Based Generated Content Data Augmentation for Remote Sensing Object Detection","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4392543853","doi":"https://doi.org/10.1109/tgrs.2024.3373442"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2024.3373442","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2024.3373442","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/A5030897484","display_name":"Yalun Dai","orcid":"https://orcid.org/0009-0001-4260-4385"},"institutions":[{"id":"https://openalex.org/I75390827","display_name":"Beijing University of Chemical Technology","ror":"https://ror.org/00df5yc52","country_code":"CN","type":"education","lineage":["https://openalex.org/I75390827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yalun Dai","raw_affiliation_strings":["College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0001-4260-4385","affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China","institution_ids":["https://openalex.org/I75390827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069637938","display_name":"Fei Ma","orcid":"https://orcid.org/0000-0003-4906-6142"},"institutions":[{"id":"https://openalex.org/I75390827","display_name":"Beijing University of Chemical Technology","ror":"https://ror.org/00df5yc52","country_code":"CN","type":"education","lineage":["https://openalex.org/I75390827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fei Ma","raw_affiliation_strings":["College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-4906-6142","affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China","institution_ids":["https://openalex.org/I75390827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100727076","display_name":"Wei Hu","orcid":"https://orcid.org/0000-0001-5320-6086"},"institutions":[{"id":"https://openalex.org/I75390827","display_name":"Beijing University of Chemical Technology","ror":"https://ror.org/00df5yc52","country_code":"CN","type":"education","lineage":["https://openalex.org/I75390827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Hu","raw_affiliation_strings":["College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China","institution_ids":["https://openalex.org/I75390827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100690860","display_name":"Fan Zhang","orcid":"https://orcid.org/0000-0002-2058-2373"},"institutions":[{"id":"https://openalex.org/I75390827","display_name":"Beijing University of Chemical Technology","ror":"https://ror.org/00df5yc52","country_code":"CN","type":"education","lineage":["https://openalex.org/I75390827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fan Zhang","raw_affiliation_strings":["College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-2058-2373","affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China","institution_ids":["https://openalex.org/I75390827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I75390827"],"apc_list":null,"apc_paid":null,"fwci":2.3958,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.88956568,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"62","issue":null,"first_page":"1","last_page":"11"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9509000182151794,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11106","display_name":"Data Management and Algorithms","score":0.9509000182151794,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9294000267982483,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9259999990463257,"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/computer-science","display_name":"Computer science","score":0.670397162437439},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.635798990726471},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5898070335388184},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.501143217086792},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.495463490486145},{"id":"https://openalex.org/keywords/content","display_name":"Content (measure theory)","score":0.4663127362728119},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4416447877883911},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.23426616191864014},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.1572883427143097}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.670397162437439},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.635798990726471},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5898070335388184},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.501143217086792},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.495463490486145},{"id":"https://openalex.org/C2778152352","wikidata":"https://www.wikidata.org/wiki/Q5165061","display_name":"Content (measure theory)","level":2,"score":0.4663127362728119},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4416447877883911},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.23426616191864014},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.1572883427143097},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2024.3373442","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2024.3373442","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/G2454424885","display_name":null,"funder_award_id":"62271034","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3692317134","display_name":null,"funder_award_id":"62201027","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":64,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W1686810756","https://openalex.org/W1982374456","https://openalex.org/W2068824491","https://openalex.org/W2076291749","https://openalex.org/W2108598243","https://openalex.org/W2110710184","https://openalex.org/W2119044918","https://openalex.org/W2193145675","https://openalex.org/W2194775991","https://openalex.org/W2512351403","https://openalex.org/W2565639579","https://openalex.org/W2603777577","https://openalex.org/W2607666785","https://openalex.org/W2765407302","https://openalex.org/W2793927960","https://openalex.org/W2915254566","https://openalex.org/W2962793481","https://openalex.org/W2963150697","https://openalex.org/W2963351448","https://openalex.org/W2964241181","https://openalex.org/W2982770724","https://openalex.org/W2989604896","https://openalex.org/W2992240579","https://openalex.org/W2992308087","https://openalex.org/W2998508940","https://openalex.org/W3009561768","https://openalex.org/W3012573144","https://openalex.org/W3035682985","https://openalex.org/W3096831136","https://openalex.org/W3106250896","https://openalex.org/W3121370741","https://openalex.org/W3169575272","https://openalex.org/W3176659256","https://openalex.org/W3184439416","https://openalex.org/W3203020760","https://openalex.org/W4205487499","https://openalex.org/W4210630409","https://openalex.org/W4226359564","https://openalex.org/W4226456028","https://openalex.org/W4252337780","https://openalex.org/W4288325606","https://openalex.org/W4292091702","https://openalex.org/W4293584584","https://openalex.org/W4299345493","https://openalex.org/W4309307768","https://openalex.org/W4313118352","https://openalex.org/W4313186194","https://openalex.org/W4386076325","https://openalex.org/W6637373629","https://openalex.org/W6741832134","https://openalex.org/W6744627333","https://openalex.org/W6750227808","https://openalex.org/W6774670964","https://openalex.org/W6779032094","https://openalex.org/W6783713337","https://openalex.org/W6784094891","https://openalex.org/W6790312409","https://openalex.org/W6798838024","https://openalex.org/W6804794748","https://openalex.org/W6810158854","https://openalex.org/W6851974562","https://openalex.org/W6853559601"],"related_works":["https://openalex.org/W4250539519","https://openalex.org/W2121524756","https://openalex.org/W4294018197","https://openalex.org/W782553550","https://openalex.org/W1987967678","https://openalex.org/W4233433299","https://openalex.org/W86540734","https://openalex.org/W2372390102","https://openalex.org/W2002113093","https://openalex.org/W4292830139"],"abstract_inverted_index":{"While":[0],"deep":[1],"learning-based":[2],"methods":[3],"have":[4],"made":[5],"significant":[6,171],"strides":[7],"in":[8,170],"remote":[9,18,31,205],"sensing":[10,19,32,206],"applications,":[11],"the":[12,24,36,45,75,114,129,132,159,184],"scarcity":[13],"and":[14,74,111,166,189,214,223],"inadequate":[15],"quality":[16],"of":[17,26,47,77,122,131],"images":[20],"tend":[21],"to":[22,42,59,62,97,195],"curtail":[23],"improvement":[25],"follow-up":[27],"research":[28],"such":[29],"as":[30,89,164,187,192],"object":[33,50,207],"detection.":[34],"However,":[35],"human":[37,70],"visual":[38],"system":[39],"is":[40,57,144,153,156,177,181],"able":[41],"quickly":[43],"grasp":[44],"features":[46],"an":[48],"unseen":[49],"given":[51],"only":[52],"a":[53,63,85,139],"few":[54],"examples,":[55],"which":[56],"considered":[58],"be":[60],"related":[61],"strong":[64],"shape":[65,108,119,134,141,160,185],"bias.":[66],"Inspired":[67],"by":[68,80],"how":[69],"toddlers":[71],"learn":[72],"shapes":[73],"process":[76],"recognizing":[78],"objects":[79],"shape,":[81],"this":[82],"paper":[83],"proposes":[84],"novel":[86],"method":[87,103,115,219],"known":[88],"Shape-Prior":[90],"based":[91],"Generated":[92],"Content":[93],"(SPGC)":[94],"data":[95,109,120,124,135,152,161,176,186,191],"augmentation":[96],"overcome":[98],"these":[99],"challenges.":[100],"Specifically,":[101],"our":[102,218],"includes":[104],"two":[105,148],"main":[106],"steps:":[107],"generation":[110],"stylization.":[112],"Initially,":[113],"begins":[116],"with":[117,183],"generating":[118],"regardless":[121],"training":[123,151,175,190],"availability.":[125],"Next,":[126],"we":[127],"enhance":[128],"robustness":[130],"generated":[133],"through":[136],"stylization,":[137],"forming":[138],"robust":[140],"dataset.":[142],"Stylization":[143],"further":[145],"bifurcated":[146],"into":[147],"scenarios:":[149],"when":[150],"unseen,":[154],"self-stylization":[155],"employed":[157],"where":[158],"simultaneously":[162],"serves":[163],"content":[165,188],"style":[167],"data,":[168],"resulting":[169],"performance":[172,222],"improvements.":[173],"When":[174],"accessible,":[178],"data-specific":[179],"stylization":[180],"applied,":[182],"style,":[193],"leading":[194],"more":[196],"substantial":[197],"enhancements":[198],"than":[199],"self-stylization.":[200],"Experimental":[201],"results":[202],"on":[203],"mainstream":[204],"detection":[208],"datasets":[209],"including":[210],"NWPU":[211],"VHR-10,":[212],"DIOR,":[213],"FAIR1M":[215],"demonstrate":[216],"that":[217],"significantly":[220],"improves":[221],"underscores":[224],"its":[225],"effectiveness.":[226]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}