{"id":"https://openalex.org/W4312465668","doi":"https://doi.org/10.1109/lgrs.2022.3230841","title":"APS-Net: An Adaptive Point Set Network for Optical Remote-Sensing Object Detection","display_name":"APS-Net: An Adaptive Point Set Network for Optical Remote-Sensing Object Detection","publication_year":2022,"publication_date":"2022-12-19","ids":{"openalex":"https://openalex.org/W4312465668","doi":"https://doi.org/10.1109/lgrs.2022.3230841"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2022.3230841","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2022.3230841","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/A5100327159","display_name":"Junfeng Zhou","orcid":"https://orcid.org/0000-0002-1054-3258"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Junfeng Zhou","raw_affiliation_strings":["Institute of Electronic Information Engineering, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Electronic Information Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102754346","display_name":"Rufei Zhang","orcid":"https://orcid.org/0000-0002-8735-3655"},"institutions":[{"id":"https://openalex.org/I202334528","display_name":"Beijing Electronic Science and Technology Institute","ror":"https://ror.org/01xdzh226","country_code":"CN","type":"education","lineage":["https://openalex.org/I202334528"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rufei Zhang","raw_affiliation_strings":["Beijing Institute of Control and Electronics Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Institute of Control and Electronics Technology, Beijing, China","institution_ids":["https://openalex.org/I202334528"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067671443","display_name":"Wei Zhao","orcid":"https://orcid.org/0000-0002-6060-1022"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Zhao","raw_affiliation_strings":["Institute of Electronic Information Engineering, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Electronic Information Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100784815","display_name":"Sheng Shen","orcid":"https://orcid.org/0000-0002-8773-6365"},"institutions":[{"id":"https://openalex.org/I202334528","display_name":"Beijing Electronic Science and Technology Institute","ror":"https://ror.org/01xdzh226","country_code":"CN","type":"education","lineage":["https://openalex.org/I202334528"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sheng Shen","raw_affiliation_strings":["Beijing Institute of Control and Electronics Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Institute of Control and Electronics Technology, Beijing, China","institution_ids":["https://openalex.org/I202334528"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100332750","display_name":"Nan Wang","orcid":"https://orcid.org/0000-0002-4062-4630"},"institutions":[{"id":"https://openalex.org/I202334528","display_name":"Beijing Electronic Science and Technology Institute","ror":"https://ror.org/01xdzh226","country_code":"CN","type":"education","lineage":["https://openalex.org/I202334528"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nan Wang","raw_affiliation_strings":["Beijing Institute of Control and Electronics Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Institute of Control and Electronics Technology, Beijing, China","institution_ids":["https://openalex.org/I202334528"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100327159"],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":1.3086,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.8179243,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"20","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":0.9986000061035156,"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":0.9986000061035156,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.994700014591217,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9937000274658203,"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/computer-science","display_name":"Computer science","score":0.8069560527801514},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.7293918132781982},{"id":"https://openalex.org/keywords/minimum-bounding-box","display_name":"Minimum bounding box","score":0.6840884685516357},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6123576164245605},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5991564989089966},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5962056517601013},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5921521782875061},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.5235136151313782},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4798811972141266},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.47062376141548157},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4631599187850952},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4614694118499756},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.4139154851436615},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.2829931378364563},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.19149845838546753},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11148533225059509}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8069560527801514},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.7293918132781982},{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.6840884685516357},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6123576164245605},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5991564989089966},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5962056517601013},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5921521782875061},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.5235136151313782},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4798811972141266},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.47062376141548157},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4631599187850952},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4614694118499756},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.4139154851436615},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2829931378364563},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.19149845838546753},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11148533225059509},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2022.3230841","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2022.3230841","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":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W2809742058","https://openalex.org/W2899594603","https://openalex.org/W2922891743","https://openalex.org/W2964979676","https://openalex.org/W2986357608","https://openalex.org/W3093319256","https://openalex.org/W3119027652","https://openalex.org/W3136761610","https://openalex.org/W3170033848","https://openalex.org/W3173658130","https://openalex.org/W3174873843","https://openalex.org/W3175496347","https://openalex.org/W3209642908","https://openalex.org/W4214648418","https://openalex.org/W4283800076","https://openalex.org/W4285189202","https://openalex.org/W4312804579","https://openalex.org/W6779586474"],"related_works":["https://openalex.org/W4237171675","https://openalex.org/W3036286480","https://openalex.org/W3192357901","https://openalex.org/W2387360586","https://openalex.org/W4287027631","https://openalex.org/W2952736415","https://openalex.org/W3209723314","https://openalex.org/W3205398323","https://openalex.org/W2883297582","https://openalex.org/W4390524233"],"abstract_inverted_index":{"Oriented":[0],"object":[1,90],"detection":[2],"in":[3,53,147,176],"optical":[4,88],"remote-sensing":[5,89,178],"images":[6],"has":[7],"been":[8],"a":[9],"challenging":[10],"task":[11],"due":[12],"to":[13,103,135,150],"arbitrary":[14],"orientations":[15],"and":[16,34,174],"densely":[17],"packed":[18],"distribution":[19,46,100],"of":[20,47,69,132],"objects.":[21],"Specifically,":[22],"most":[23],"existing":[24],"methods":[25],"lack":[26],"adaptivity":[27],"when":[28],"regressing":[29],"objects":[30],"with":[31],"different":[32],"shapes":[33],"orientations.":[35],"Although":[36],"the":[37,44,48,61,72,98,105,112,116,123,130,142,148,177],"point":[38,49,62,113,133],"set":[39,50,63,114],"representation":[40],"is":[41,51],"relatively":[42],"flexible,":[43],"initial":[45,99,107],"fixed":[52],"advance.":[54],"In":[55,76],"addition,":[56],"some":[57],"models":[58],"based":[59],"on":[60,166],"cannot":[64],"get":[65],"high":[66],"location":[67,134,137],"precision":[68],"points,":[70],"affecting":[71],"bounding":[73],"box":[74],"generation.":[75],"this":[77],"letter,":[78],"we":[79,96,121,140],"propose":[80,97],"an":[81],"Adaptive":[82],"Point":[83],"Set":[84],"Network":[85],"(APS-Net)":[86],"for":[87],"detection,":[91],"including":[92],"three":[93,167],"improvements.":[94],"First,":[95],"learner":[101],"(IDL)":[102],"learn":[104],"optimal":[106],"aspect":[108],"ratio,":[109],"which":[110,128],"helps":[111],"fit":[115],"object\u2019s":[117],"shape":[118],"well.":[119],"Second,":[120],"design":[122],"uncertainty":[124,131],"measurement":[125],"module":[126],"(UMM),":[127],"considers":[129],"improve":[136],"precision.":[138],"Third,":[139],"introduce":[141],"local":[143],"outlier":[144,152],"factor":[145],"(LOF)":[146],"loss":[149],"punish":[151],"points":[153],"more":[154],"reasonably.":[155],"Extensive":[156],"experiments":[157],"demonstrate":[158],"that":[159],"our":[160],"proposed":[161],"model":[162],"achieves":[163],"state-of-the-art":[164],"performance":[165],"commonly":[168],"used":[169],"datasets":[170],"(i.e.,":[171],"DOTA-v1.0,":[172],"UCAS-AOD,":[173],"HRSC2016)":[175],"field.":[179]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":7}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
