{"id":"https://openalex.org/W3098042825","doi":"https://doi.org/10.1109/lgrs.2020.3035844","title":"Train in Dense and Test in Sparse: A Method for Sparse Object Detection in Aerial Images","display_name":"Train in Dense and Test in Sparse: A Method for Sparse Object Detection in Aerial Images","publication_year":2020,"publication_date":"2020-11-11","ids":{"openalex":"https://openalex.org/W3098042825","doi":"https://doi.org/10.1109/lgrs.2020.3035844","mag":"3098042825"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2020.3035844","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2020.3035844","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"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 Geoscience and Remote Sensing Letters","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/A5101664456","display_name":"Kun Ding","orcid":"https://orcid.org/0000-0002-2256-8815"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kun Ding","raw_affiliation_strings":["Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-2256-8815","affiliations":[{"raw_affiliation_string":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048350041","display_name":"Guojin He","orcid":"https://orcid.org/0000-0001-7225-7276"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guojin He","raw_affiliation_strings":["Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-7225-7276","affiliations":[{"raw_affiliation_string":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011036865","display_name":"Huxiang Gu","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huxiang Gu","raw_affiliation_strings":["National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101677557","display_name":"Zisha Zhong","orcid":"https://orcid.org/0000-0002-2086-8435"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zisha Zhong","raw_affiliation_strings":["National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-2086-8435","affiliations":[{"raw_affiliation_string":"National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040673285","display_name":"Shiming Xiang","orcid":"https://orcid.org/0000-0002-2089-9733"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shiming Xiang","raw_affiliation_strings":["National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-2089-9733","affiliations":[{"raw_affiliation_string":"National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100435212","display_name":"Chunhong Pan","orcid":"https://orcid.org/0000-0001-7433-4474"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunhong Pan","raw_affiliation_strings":["National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2937,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.58053947,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"19","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9986000061035156,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9954000115394592,"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":0.8099663257598877},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7653684020042419},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.7108241319656372},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6196911334991455},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5407505035400391},{"id":"https://openalex.org/keywords/aerial-image","display_name":"Aerial image","score":0.5299908518791199},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5208359360694885},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48580265045166016},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.478794664144516},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4573255777359009},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.44056305289268494},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.31206220388412476}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8099663257598877},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7653684020042419},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.7108241319656372},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6196911334991455},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5407505035400391},{"id":"https://openalex.org/C2776429412","wikidata":"https://www.wikidata.org/wiki/Q4688011","display_name":"Aerial image","level":3,"score":0.5299908518791199},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5208359360694885},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48580265045166016},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.478794664144516},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4573255777359009},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.44056305289268494},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.31206220388412476},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2020.3035844","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2020.3035844","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"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 Geoscience and Remote Sensing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3246091792","display_name":null,"funder_award_id":"XDA19090300","funder_id":"https://openalex.org/F4320321133","funder_display_name":"Chinese Academy of Sciences"},{"id":"https://openalex.org/G5538849239","display_name":"\u57fa\u4e8e\u8ba4\u77e5\u8ba1\u7b97\u7684\u9065\u611f\u536b\u661f\u4e0b\u884c\u6570\u636e\u5373\u65f6\u670d\u52a1\u7684\u7406\u8bba\u4e0e\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61731022","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/F4320321133","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W2013081398","https://openalex.org/W2066916495","https://openalex.org/W2156338447","https://openalex.org/W2756626859","https://openalex.org/W2792542990","https://openalex.org/W2897529137","https://openalex.org/W2899594603","https://openalex.org/W2920582597","https://openalex.org/W2924873663","https://openalex.org/W2963182550","https://openalex.org/W2963346150","https://openalex.org/W2963351448","https://openalex.org/W2964241181","https://openalex.org/W2966394087","https://openalex.org/W2975773621","https://openalex.org/W2982164728","https://openalex.org/W2982770724","https://openalex.org/W2983056308","https://openalex.org/W2988916019","https://openalex.org/W2989604896","https://openalex.org/W2994619704","https://openalex.org/W3034993937","https://openalex.org/W3103461182","https://openalex.org/W3177105943","https://openalex.org/W3208645658","https://openalex.org/W4250482878","https://openalex.org/W4293584584","https://openalex.org/W4304206535","https://openalex.org/W6750227808","https://openalex.org/W6776984768"],"related_works":["https://openalex.org/W2972256598","https://openalex.org/W4388964477","https://openalex.org/W4388813151","https://openalex.org/W2610408157","https://openalex.org/W4221156520","https://openalex.org/W2099047584","https://openalex.org/W2612465689","https://openalex.org/W4327521163","https://openalex.org/W4237245474","https://openalex.org/W4387801831"],"abstract_inverted_index":{"Applications":[0],"of":[1,35,68,77,109],"aerial":[2,8,31,56,78,98],"imaging,":[3],"especially":[4],"based":[5],"on":[6,151],"unmanned":[7],"vehicles":[9],"(UAVs)":[10],"platform,":[11],"rapidly":[12],"explode":[13],"in":[14,30,50,55,72,87,91,97,102,124,139],"recent":[15],"years.":[16],"Meanwhile,":[17],"vision-based":[18],"sensing,":[19],"e.g.,":[20],"detection":[21,58,75],"and":[22,89,122,141],"recognition,":[23],"for":[24],"UAVs":[25],"becomes":[26],"increasingly":[27],"important.":[28],"Objects":[29],"images":[32,46],"are":[33,47,111],"usually":[34],"tiny":[36],"size,":[37],"hence":[38],"occupying":[39],"a":[40,70,83,115],"limited":[41],"area.":[42],"Terminology":[43],"speaking,":[44],"the":[45,66,74,103,106,125,131,152,159,178],"very":[48],"sparse":[49,92,146],"spatial.":[51],"However,":[52],"existing":[53],"work":[54],"object":[57,99,110,133],"commonly":[59],"ignores":[60],"this":[61],"point.":[62],"Conversely,":[63],"we":[64,81,156,175],"explore":[65],"availability":[67],"such":[69],"property":[71],"improving":[73],"performance":[76],"images.":[79],"Specifically,":[80],"propose":[82],"general":[84],"method,":[85],"train":[86],"dense":[88],"test":[90],"(TDTS),":[93],"to":[94,135,165,171],"exploit":[95],"sparsity":[96,160,179],"detection:":[100],"1)":[101],"training":[104,114],"stage,":[105,127],"possible":[107,132],"positions":[108],"learned":[112],"by":[113,145],"fully":[116],"convolutional":[117],"network":[118],"(called":[119],"prophet":[120,128],"head)":[121],"2)":[123],"testing":[126],"head":[129,144],"identifies":[130],"locations":[134],"reduce":[136],"redundant":[137],"computation":[138],"classification":[140],"box":[142],"prediction":[143],"convolution.":[147],"By":[148],"extensive":[149],"experiments":[150],"VisDrone2019-Det":[153],"data":[154],"set,":[155],"find":[157],"that":[158,177],"can":[161],"not":[162],"only":[163],"help":[164],"speed":[166],"up":[167],"inference":[168],"but":[169],"also":[170],"improve":[172],"accuracy.":[173],"Thus,":[174],"argue":[176],"deserves":[180],"more":[181],"attention.":[182]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
