{"id":"https://openalex.org/W4206294875","doi":"https://doi.org/10.3390/rs14020420","title":"Small Object Detection Method Based on Adaptive Spatial Parallel Convolution and Fast Multi-Scale Fusion","display_name":"Small Object Detection Method Based on Adaptive Spatial Parallel Convolution and Fast Multi-Scale Fusion","publication_year":2022,"publication_date":"2022-01-17","ids":{"openalex":"https://openalex.org/W4206294875","doi":"https://doi.org/10.3390/rs14020420"},"language":"en","primary_location":{"id":"doi:10.3390/rs14020420","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14020420","pdf_url":"https://www.mdpi.com/2072-4292/14/2/420/pdf?version=1642418190","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"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":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/14/2/420/pdf?version=1642418190","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5006116691","display_name":"Guanqiu Qi","orcid":"https://orcid.org/0000-0001-9562-3865"},"institutions":[{"id":"https://openalex.org/I115441956","display_name":"Buffalo State University","ror":"https://ror.org/05ms04m92","country_code":"US","type":"education","lineage":["https://openalex.org/I115441956"]},{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Guanqiu Qi","raw_affiliation_strings":["Computer Information Systems Department, State University of New York at Buffalo State, Buffalo, NY 14222, USA"],"affiliations":[{"raw_affiliation_string":"Computer Information Systems Department, State University of New York at Buffalo State, Buffalo, NY 14222, USA","institution_ids":["https://openalex.org/I63190737","https://openalex.org/I115441956"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046385058","display_name":"Yuanchuan Zhang","orcid":"https://orcid.org/0000-0003-2660-8324"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanchuan Zhang","raw_affiliation_strings":["College of Automation, Chongqing University of Posts and Telecommunications, Chongqing 400065, China"],"affiliations":[{"raw_affiliation_string":"College of Automation, Chongqing University of Posts and Telecommunications, Chongqing 400065, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100676184","display_name":"Kunpeng Wang","orcid":"https://orcid.org/0000-0002-7871-624X"},"institutions":[{"id":"https://openalex.org/I1297991670","display_name":"Southwest University of Science and Technology","ror":"https://ror.org/04d996474","country_code":"CN","type":"education","lineage":["https://openalex.org/I1297991670"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Kunpeng Wang","raw_affiliation_strings":["School of Information Engineering, Southwest University of Science and Technology, Mianyang 621010, China"],"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Southwest University of Science and Technology, Mianyang 621010, China","institution_ids":["https://openalex.org/I1297991670"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023273216","display_name":"Neal Mazur","orcid":"https://orcid.org/0000-0002-6471-2934"},"institutions":[{"id":"https://openalex.org/I115441956","display_name":"Buffalo State University","ror":"https://ror.org/05ms04m92","country_code":"US","type":"education","lineage":["https://openalex.org/I115441956"]},{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Neal Mazur","raw_affiliation_strings":["Computer Information Systems Department, State University of New York at Buffalo State, Buffalo, NY 14222, USA"],"affiliations":[{"raw_affiliation_string":"Computer Information Systems Department, State University of New York at Buffalo State, Buffalo, NY 14222, USA","institution_ids":["https://openalex.org/I63190737","https://openalex.org/I115441956"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100355854","display_name":"Yang Liu","orcid":"https://orcid.org/0000-0002-3295-2917"},"institutions":[{"id":"https://openalex.org/I4210100976","display_name":"BOE Technology Group (China)","ror":"https://ror.org/01cwwvj38","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210100976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Liu","raw_affiliation_strings":["BOE Technology Group Co., Ltd., Chongqing 400799, China"],"affiliations":[{"raw_affiliation_string":"BOE Technology Group Co., Ltd., Chongqing 400799, China","institution_ids":["https://openalex.org/I4210100976"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070156877","display_name":"Devanshi Malaviya","orcid":null},"institutions":[{"id":"https://openalex.org/I115441956","display_name":"Buffalo State University","ror":"https://ror.org/05ms04m92","country_code":"US","type":"education","lineage":["https://openalex.org/I115441956"]},{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Devanshi Malaviya","raw_affiliation_strings":["Computer Information Systems Department, State University of New York at Buffalo State, Buffalo, NY 14222, USA"],"affiliations":[{"raw_affiliation_string":"Computer Information Systems Department, State University of New York at Buffalo State, Buffalo, NY 14222, USA","institution_ids":["https://openalex.org/I63190737","https://openalex.org/I115441956"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100676184"],"corresponding_institution_ids":["https://openalex.org/I1297991670"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":13.143,"has_fulltext":false,"cited_by_count":135,"citation_normalized_percentile":{"value":0.99312557,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"14","issue":"2","first_page":"420","last_page":"420"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998000264167786,"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":0.9998000264167786,"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9954000115394592,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9916999936103821,"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":0.8291757106781006},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6609902381896973},{"id":"https://openalex.org/keywords/upsampling","display_name":"Upsampling","score":0.6561089158058167},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6372702121734619},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.48201027512550354},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4750744700431824},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.47209566831588745},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.46797114610671997},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45815718173980713},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.4530446529388428},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4435702860355377},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.1408044695854187},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1041976809501648}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8291757106781006},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6609902381896973},{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.6561089158058167},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6372702121734619},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.48201027512550354},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4750744700431824},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.47209566831588745},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.46797114610671997},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45815718173980713},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4530446529388428},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4435702860355377},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.1408044695854187},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1041976809501648},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"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":3,"locations":[{"id":"doi:10.3390/rs14020420","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14020420","pdf_url":"https://www.mdpi.com/2072-4292/14/2/420/pdf?version=1642418190","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"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":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:b17d8a0b658c4f51b87dc545c2135f2b","is_oa":true,"landing_page_url":"https://doaj.org/article/b17d8a0b658c4f51b87dc545c2135f2b","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 14, Iss 2, p 420 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/14/2/420/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs14020420","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":"Remote Sensing; Volume 14; Issue 2; Pages: 420","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs14020420","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14020420","pdf_url":"https://www.mdpi.com/2072-4292/14/2/420/pdf?version=1642418190","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"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":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4206294875.pdf","grobid_xml":"https://content.openalex.org/works/W4206294875.grobid-xml"},"referenced_works_count":45,"referenced_works":["https://openalex.org/W1677182931","https://openalex.org/W1836465849","https://openalex.org/W1861492603","https://openalex.org/W2031489346","https://openalex.org/W2193145675","https://openalex.org/W2194775991","https://openalex.org/W2474309084","https://openalex.org/W2476548250","https://openalex.org/W2479866714","https://openalex.org/W2565639579","https://openalex.org/W2625219738","https://openalex.org/W2753588254","https://openalex.org/W2919046835","https://openalex.org/W2921528463","https://openalex.org/W2922509574","https://openalex.org/W2924873663","https://openalex.org/W2925359305","https://openalex.org/W2962721361","https://openalex.org/W2962766617","https://openalex.org/W2962777203","https://openalex.org/W2962917547","https://openalex.org/W2963351448","https://openalex.org/W2963604034","https://openalex.org/W2963658551","https://openalex.org/W2963857746","https://openalex.org/W2964093967","https://openalex.org/W2964350391","https://openalex.org/W2966926453","https://openalex.org/W2985384565","https://openalex.org/W2996603555","https://openalex.org/W3009131247","https://openalex.org/W3009396058","https://openalex.org/W3011919688","https://openalex.org/W3034971973","https://openalex.org/W3106250896","https://openalex.org/W3107034740","https://openalex.org/W3121020412","https://openalex.org/W3128340563","https://openalex.org/W3136957409","https://openalex.org/W3158141244","https://openalex.org/W3176085218","https://openalex.org/W3192459570","https://openalex.org/W6761306150","https://openalex.org/W6762585180","https://openalex.org/W6786661815"],"related_works":["https://openalex.org/W2062399876","https://openalex.org/W2607795551","https://openalex.org/W3155117723","https://openalex.org/W1991429770","https://openalex.org/W1983892167","https://openalex.org/W2281134365","https://openalex.org/W4310746709","https://openalex.org/W4386075645","https://openalex.org/W3088721469","https://openalex.org/W4212888438"],"abstract_inverted_index":{"As":[0],"one":[1],"type":[2],"of":[3,47,87,123,138,155,188],"object":[4,7,27,43,60,173,190],"detection,":[5],"small":[6,42,59,172,189],"detection":[8,28,44,61,174,191],"has":[9],"been":[10],"widely":[11],"used":[12],"in":[13,34,41],"daily-life-related":[14],"applications":[15],"with":[16],"many":[17],"real-time":[18,51,200],"requirements,":[19],"such":[20],"as":[21],"autopilot":[22],"and":[23,45,70,93,141,164,196],"navigation.":[24],"Although":[25],"deep-learning-based":[26],"methods":[29],"have":[30],"achieved":[31],"great":[32],"success":[33],"recent":[35],"years,":[36],"they":[37],"are":[38],"not":[39],"effective":[40],"most":[46],"them":[48],"cannot":[49],"achieve":[50],"processing.":[52],"Therefore,":[53],"this":[54],"paper":[55],"proposes":[56],"a":[57,111,198],"single-stage":[58],"network":[62,163],"(SODNet)":[63],"that":[64,180],"integrates":[65],"the":[66,85,96,106,120,135,153,156,162,171,181,186],"specialized":[67],"feature":[68,107,158],"extraction":[69,108],"information":[71,89,99],"fusion":[72,128,137],"techniques.":[73],"An":[74],"adaptively":[75,94],"spatial":[76,88,98,142],"parallel":[77],"convolution":[78],"module":[79,129],"(ASPConv)":[80],"is":[81,115,131],"proposed":[82,116,132,182],"to":[83,117,133,150],"alleviate":[84,134],"lack":[86],"for":[90],"target":[91],"objects":[92],"obtain":[95],"corresponding":[97],"through":[100],"multi-scale":[101,127,157],"receptive":[102],"fields,":[103],"thereby":[104,168],"improving":[105,170],"ability.":[109,175],"Additionally,":[110],"split-fusion":[112],"sub-module":[113],"(SF)":[114],"effectively":[118,169],"reduce":[119],"time":[121],"complexity":[122],"ASPConv.":[124],"A":[125],"fast":[126,147],"(FMF)":[130],"insufficient":[136],"both":[139],"semantic":[140],"information.":[143],"FMF":[144],"uses":[145],"two":[146],"upsampling":[148],"operators":[149],"first":[151],"unify":[152],"resolution":[154],"maps":[159],"extracted":[160],"by":[161],"then":[165],"fuse":[166],"them,":[167],"Comparative":[176],"experimental":[177],"results":[178],"prove":[179],"method":[183],"considerably":[184],"improves":[185],"accuracy":[187],"on":[192],"multiple":[193],"benchmark":[194],"datasets":[195],"achieves":[197],"high":[199],"performance.":[201]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":51},{"year":2024,"cited_by_count":31},{"year":2023,"cited_by_count":32},{"year":2022,"cited_by_count":15}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2022-01-25T00:00:00"}