{"id":"https://openalex.org/W4406611853","doi":"https://doi.org/10.1109/smc54092.2024.10831911","title":"Detecting Small Objects using Multi-Scale Feature Fusion Mechanism with Convolutional Block Attention","display_name":"Detecting Small Objects using Multi-Scale Feature Fusion Mechanism with Convolutional Block Attention","publication_year":2024,"publication_date":"2024-10-06","ids":{"openalex":"https://openalex.org/W4406611853","doi":"https://doi.org/10.1109/smc54092.2024.10831911"},"language":"en","primary_location":{"id":"doi:10.1109/smc54092.2024.10831911","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc54092.2024.10831911","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5007977316","display_name":"Xionglong Li","orcid":null},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xionglong Li","raw_affiliation_strings":["School of Computer Science and Technology, Hangzhou Dianzi Uni-versity,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Hangzhou Dianzi Uni-versity,China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100691443","display_name":"Kun Yang","orcid":"https://orcid.org/0000-0002-8224-5161"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kun Yang","raw_affiliation_strings":["School of Computer Science and Technology, Hangzhou Dianzi Uni-versity,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Hangzhou Dianzi Uni-versity,China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029499523","display_name":"Rui Huang","orcid":"https://orcid.org/0000-0002-7950-1662"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rui Huang","raw_affiliation_strings":["Internationlization SandD and Measurement Platform, Coupang, Inc.,Shanghai,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Internationlization SandD and Measurement Platform, Coupang, Inc.,Shanghai,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Binqin Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Binqin Zhou","raw_affiliation_strings":["School of Computer Science and Technology, Hangzhou Dianzi Uni-versity,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Hangzhou Dianzi Uni-versity,China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jincheng Xiao","orcid":null},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jincheng Xiao","raw_affiliation_strings":["School of Computer Science and Technology, Hangzhou Dianzi Uni-versity,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Hangzhou Dianzi Uni-versity,China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074351178","display_name":"Zhigang Gao","orcid":"https://orcid.org/0000-0003-3760-357X"},"institutions":[{"id":"https://openalex.org/I55538621","display_name":"China Jiliang University","ror":"https://ror.org/05v1y0t93","country_code":"CN","type":"education","lineage":["https://openalex.org/I55538621"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhigang Gao","raw_affiliation_strings":["College of Information Engineering, China Jiliang University,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Engineering, China Jiliang University,China","institution_ids":["https://openalex.org/I55538621"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4620","last_page":"4625"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14257","display_name":"Advanced Measurement and Detection Methods","score":0.9297000169754028,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T14257","display_name":"Advanced Measurement and Detection Methods","score":0.9297000169754028,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9197999835014343,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9186000227928162,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7194666266441345},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.6814330816268921},{"id":"https://openalex.org/keywords/mechanism","display_name":"Mechanism (biology)","score":0.6382843255996704},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5072395205497742},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4976253807544708},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4793037474155426},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.4472275972366333},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4428289532661438},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44246476888656616},{"id":"https://openalex.org/keywords/fusion-mechanism","display_name":"Fusion mechanism","score":0.4323320686817169},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07309818267822266},{"id":"https://openalex.org/keywords/lipid-bilayer-fusion","display_name":"Lipid bilayer fusion","score":0.054291605949401855},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.053214699029922485}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7194666266441345},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.6814330816268921},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.6382843255996704},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5072395205497742},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4976253807544708},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4793037474155426},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.4472275972366333},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4428289532661438},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44246476888656616},{"id":"https://openalex.org/C173414695","wikidata":"https://www.wikidata.org/wiki/Q5510276","display_name":"Fusion mechanism","level":4,"score":0.4323320686817169},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07309818267822266},{"id":"https://openalex.org/C103038307","wikidata":"https://www.wikidata.org/wiki/Q6556360","display_name":"Lipid bilayer fusion","level":3,"score":0.054291605949401855},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.053214699029922485},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smc54092.2024.10831911","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc54092.2024.10831911","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2133050864","display_name":"\u57fa\u4e8e\u7528\u6237\u53cd\u9988\u7279\u5f81\u9884\u6d4b\u7684\u7ec6\u7c92\u5ea6\u56fe\u50cf\u5206\u7c7b\u7814\u7a76","funder_award_id":"61972119","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2565639579","https://openalex.org/W2570343428","https://openalex.org/W2884585870","https://openalex.org/W2962766617","https://openalex.org/W2963037989","https://openalex.org/W2963351448","https://openalex.org/W2963857746","https://openalex.org/W2964241181","https://openalex.org/W3208645658","https://openalex.org/W4213076145","https://openalex.org/W4220827132"],"related_works":["https://openalex.org/W2788292821","https://openalex.org/W2988498288","https://openalex.org/W1991764124","https://openalex.org/W2786308501","https://openalex.org/W2012247345","https://openalex.org/W4318719019","https://openalex.org/W2145243726","https://openalex.org/W2463550667","https://openalex.org/W2351649588","https://openalex.org/W4378188910"],"abstract_inverted_index":{"Small":[0],"object":[1,151],"detection":[2],"is":[3],"difficult":[4],"because":[5],"of":[6,13,21,33,79,149],"their":[7],"low":[8,58],"resolution":[9],"and":[10,30,68,127],"the":[11,19,31,46,57,65,69,76,80,85,91,96,102,106,116,121,128,139,147],"inclusion":[12],"unimportant":[14],"background":[15,34],"information.":[16],"Aiming":[17],"at":[18],"problem":[20],"small":[22,132,150],"objects":[23,133],"information":[24,61,83],"loss":[25],"in":[26,136],"multiscale":[27],"feature":[28,41,60,71,82,98,107],"fusion":[29,42,72,103],"impact":[32],"information,":[35,99],"this":[36],"paper":[37],"proposes":[38],"a":[39],"multi-scale":[40],"mechanism":[43,89],"(MFFM)":[44],"with":[45],"convolutional":[47],"block":[48],"attention":[49,86],"modules":[50],"(CBAM).":[51],"The":[52,109],"proposed":[53],"approach":[54,144],"efficiently":[55],"utilizes":[56],"three-layer":[59,97],"(P1-P3)":[62],"output":[63],"from":[64],"backbone":[66],"network":[67],"improved":[70],"technique":[73],"to":[74,94,138],"enhance":[75],"characterization":[77],"ability":[78,104],"single-layer":[81,92],"through":[84],"mechanism.":[87],"This":[88,143],"enables":[90],"features":[93],"carry":[95],"thereby":[100],"improving":[101],"among":[105],"layers.":[108],"experimental":[110],"results":[111],"demonstrate":[112],"that":[113],"MFFM":[114],"enhances":[115],"overall":[117],"accuracy":[118,129],"mAP":[119],"on":[120,131],"VisDrone2019-DET":[122],"validation":[123],"set":[124],"by":[125,134],"1.4%":[126],"APs":[130],"1.5%":[135],"comparison":[137],"baseline":[140],"model":[141],"YOLOX-X.":[142],"effectively":[145],"improves":[146],"performance":[148],"detection.":[152]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
