{"id":"https://openalex.org/W3103135921","doi":"https://doi.org/10.3390/s20226530","title":"AF-SSD: An Accurate and Fast Single Shot Detector for High Spatial Remote Sensing Imagery","display_name":"AF-SSD: An Accurate and Fast Single Shot Detector for High Spatial Remote Sensing Imagery","publication_year":2020,"publication_date":"2020-11-15","ids":{"openalex":"https://openalex.org/W3103135921","doi":"https://doi.org/10.3390/s20226530","mag":"3103135921","pmid":"https://pubmed.ncbi.nlm.nih.gov/33203129"},"language":"en","primary_location":{"id":"doi:10.3390/s20226530","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s20226530","pdf_url":"https://www.mdpi.com/1424-8220/20/22/6530/pdf?version=1605431490","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/20/22/6530/pdf?version=1605431490","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5041523465","display_name":"Ruihong Yin","orcid":"https://orcid.org/0000-0001-5989-8976"},"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":"Ruihong Yin","raw_affiliation_strings":["School of Electronic and Information Engineering, Beihang University, Beijing 100191, China"],"raw_orcid":"https://orcid.org/0000-0001-5989-8976","affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Beihang University, Beijing 100191, China","institution_ids":["https://openalex.org/I82880672"]}]},{"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":["School of Electronic and Information Engineering, Beihang University, Beijing 100191, China"],"raw_orcid":"https://orcid.org/0000-0002-6060-1022","affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Beihang University, Beijing 100191, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037630663","display_name":"Xudong Fan","orcid":"https://orcid.org/0000-0003-1363-9834"},"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":"Xudong Fan","raw_affiliation_strings":["School of Electronic and Information Engineering, Beihang University, Beijing 100191, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Beihang University, Beijing 100191, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100715069","display_name":"Yongfeng Yin","orcid":"https://orcid.org/0000-0001-9432-3051"},"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":"Yongfeng Yin","raw_affiliation_strings":["School of Reliability and Systems Engineering, Beihang University, Beijing 100191, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Reliability and Systems Engineering, Beihang University, Beijing 100191, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5100715069"],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2673},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2673},"fwci":0.8661,"has_fulltext":true,"cited_by_count":18,"citation_normalized_percentile":{"value":0.73683658,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"20","issue":"22","first_page":"6530","last_page":"6530"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9993000030517578,"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":0.9993000030517578,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9991999864578247,"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":0.9969000220298767,"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":0.8107629418373108},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6035498976707458},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.60140061378479},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.5604453086853027},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.5577806234359741},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.5402661561965942},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5360880494117737},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.533836305141449},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5185842514038086},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.5166240334510803},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5019810199737549},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4948100447654724},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.449216365814209},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4405983090400696},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.43074965476989746},{"id":"https://openalex.org/keywords/geospatial-analysis","display_name":"Geospatial analysis","score":0.4262970983982086},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3862517178058624},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3779587745666504},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.07378920912742615}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8107629418373108},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6035498976707458},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.60140061378479},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.5604453086853027},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.5577806234359741},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.5402661561965942},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5360880494117737},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.533836305141449},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5185842514038086},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.5166240334510803},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5019810199737549},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4948100447654724},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.449216365814209},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4405983090400696},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.43074965476989746},{"id":"https://openalex.org/C9770341","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Geospatial analysis","level":2,"score":0.4262970983982086},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3862517178058624},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3779587745666504},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.07378920912742615},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/s20226530","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s20226530","pdf_url":"https://www.mdpi.com/1424-8220/20/22/6530/pdf?version=1605431490","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:33203129","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33203129","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:f31d35c796f548cabe100579ce102a0b","is_oa":true,"landing_page_url":"https://doaj.org/article/f31d35c796f548cabe100579ce102a0b","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 20, Iss 22, p 6530 (2020)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/20/22/6530/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s20226530","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors; Volume 20; Issue 22; Pages: 6530","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:7697322","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7697322","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s20226530","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s20226530","pdf_url":"https://www.mdpi.com/1424-8220/20/22/6530/pdf?version=1605431490","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4212455486","display_name":null,"funder_award_id":"20170751006","funder_id":"https://openalex.org/F4320327472","funder_display_name":"Chinese Aeronautical Establishment"}],"funders":[{"id":"https://openalex.org/F4320309475","display_name":"Northwestern University","ror":"https://ror.org/000e0be47"},{"id":"https://openalex.org/F4320321392","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86"},{"id":"https://openalex.org/F4320327472","display_name":"Chinese Aeronautical Establishment","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3103135921.pdf","grobid_xml":"https://content.openalex.org/works/W3103135921.grobid-xml"},"referenced_works_count":44,"referenced_works":["https://openalex.org/W1536680647","https://openalex.org/W1665214252","https://openalex.org/W1677182931","https://openalex.org/W1686810756","https://openalex.org/W1861492603","https://openalex.org/W2005368619","https://openalex.org/W2031489346","https://openalex.org/W2088049833","https://openalex.org/W2108598243","https://openalex.org/W2144506857","https://openalex.org/W2183182206","https://openalex.org/W2193145675","https://openalex.org/W2400138547","https://openalex.org/W2407521645","https://openalex.org/W2490270993","https://openalex.org/W2512351403","https://openalex.org/W2565639579","https://openalex.org/W2570343428","https://openalex.org/W2579152745","https://openalex.org/W2599765304","https://openalex.org/W2613718673","https://openalex.org/W2733535455","https://openalex.org/W2743473392","https://openalex.org/W2773495332","https://openalex.org/W2783808331","https://openalex.org/W2792824754","https://openalex.org/W2797527871","https://openalex.org/W2883780447","https://openalex.org/W2894651257","https://openalex.org/W2908113397","https://openalex.org/W2911631403","https://openalex.org/W2921357635","https://openalex.org/W2926837263","https://openalex.org/W2949117887","https://openalex.org/W2949436339","https://openalex.org/W2953106684","https://openalex.org/W2962749812","https://openalex.org/W2963037989","https://openalex.org/W2963150697","https://openalex.org/W2963300223","https://openalex.org/W2963351448","https://openalex.org/W2963604034","https://openalex.org/W2988452521","https://openalex.org/W3106250896"],"related_works":["https://openalex.org/W2180954594","https://openalex.org/W2052835778","https://openalex.org/W4367313141","https://openalex.org/W2049003611","https://openalex.org/W2127804977","https://openalex.org/W2004086023","https://openalex.org/W2108418243","https://openalex.org/W164103134","https://openalex.org/W4401575149","https://openalex.org/W4313263731"],"abstract_inverted_index":{"There":[0],"are":[1,30,50,54],"a":[2,99,137,168,207],"large":[3],"number":[4,105],"of":[5,31,106,109,206],"studies":[6],"on":[7,17,70,220,232,256,258],"geospatial":[8],"object":[9,71],"detection.":[10,72],"However,":[11],"many":[12],"existing":[13],"methods":[14],"only":[15],"focus":[16],"either":[18],"accuracy":[19,29],"or":[20],"speed.":[21],"Methods":[22],"with":[23,64,171,179],"both":[24],"fast":[25,81],"speed":[26],"and":[27,39,41,56,60,80,121,130,150,173,185,226,251],"high":[28,87,133],"great":[32],"importance":[33],"in":[34],"some":[35,51,119],"scenes,":[36],"like":[37],"search":[38],"rescue,":[40],"military":[42],"information":[43,129,161],"acquisition.":[44],"In":[45,73,112],"remote":[46,89],"sensing":[47,90],"images,":[48],"there":[49],"targets":[52,146,178],"that":[53,238],"small":[55,145],"have":[57],"few":[58,186],"textures":[59,187],"low":[61,180],"contrast":[62,181],"compared":[63],"the":[65,104,110,132,153,210,216,233],"background,":[66],"which":[67],"impose":[68],"challenges":[69],"this":[74,113],"paper,":[75],"we":[76,97,116,166],"propose":[77],"an":[78,259],"accurate":[79],"single":[82],"shot":[83],"detector":[84],"(AF-SSD)":[85],"for":[86,177,199,224],"spatial":[88,172,192],"imagery":[91],"to":[92,102,125,143,162,218],"solve":[93],"these":[94],"problems.":[95],"Firstly,":[96],"design":[98,167],"lightweight":[100,114],"backbone":[101],"reduce":[103],"trainable":[107],"parameters":[108,246],"network.":[111],"backbone,":[115],"also":[117],"use":[118],"wide":[120],"deep":[122],"convolutional":[123],"blocks":[124],"extract":[126,196],"more":[127],"semantic":[128,160],"keep":[131],"detection":[134,244],"precision.":[135],"Secondly,":[136],"novel":[138],"encoding-decoding":[139,154],"module":[140,155,194,213],"is":[141],"employed":[142],"detect":[144],"accurately.":[147],"With":[148],"up-sampling":[149],"summation":[151],"operations,":[152],"can":[156,195,214],"add":[157],"strong":[158],"high-level":[159],"low-level":[163],"features.":[164],"Thirdly,":[165],"cascade":[169],"structure":[170],"channel":[174,205,211],"attention":[175,193,212],"modules":[176],"(named":[182,188],"low-contrast":[183,225],"targets)":[184],"few-texture":[189,200,227],"targets).":[190],"The":[191,229],"long-range":[197],"features":[198,223],"targets.":[201,228],"By":[202],"weighting":[203],"each":[204],"feature":[208],"map,":[209],"guide":[215],"network":[217],"concentrate":[219],"easily":[221],"identifiable":[222],"experimental":[230],"results":[231],"NWPU":[234],"VHR-10":[235],"dataset":[236],"show":[237],"our":[239],"proposed":[240],"AF-SSD":[241],"achieves":[242],"superior":[243],"performance:":[245],"5.7":[247],"M,":[248],"mAP":[249],"88.7%,":[250],"0.035":[252],"s":[253],"per":[254],"image":[255],"average":[257],"NVIDIA":[260],"GTX-1080Ti":[261],"GPU.":[262]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":5}],"updated_date":"2026-07-30T17:31:21.811387","created_date":"2025-10-10T00:00:00"}