{"id":"https://openalex.org/W3209387261","doi":"https://doi.org/10.1109/icspcc52875.2021.9564438","title":"Airport Small Target Algorithm Based on Convolution Kernel Attention Mechanism","display_name":"Airport Small Target Algorithm Based on Convolution Kernel Attention Mechanism","publication_year":2021,"publication_date":"2021-08-17","ids":{"openalex":"https://openalex.org/W3209387261","doi":"https://doi.org/10.1109/icspcc52875.2021.9564438","mag":"3209387261"},"language":"en","primary_location":{"id":"doi:10.1109/icspcc52875.2021.9564438","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icspcc52875.2021.9564438","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC)","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/A5082815648","display_name":"Shichong Li","orcid":null},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shichong Li","raw_affiliation_strings":["School of Information Science and Engineering, Yunnan University, KunMing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Yunnan University, KunMing, China","institution_ids":["https://openalex.org/I189210763"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101465215","display_name":"Hao Zhou","orcid":"https://orcid.org/0000-0002-1012-3042"},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Zhou","raw_affiliation_strings":["School of Information Science and Engineering, Yunnan University, KunMing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Yunnan University, KunMing, China","institution_ids":["https://openalex.org/I189210763"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I189210763"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"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":0.9975000023841858,"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":0.9975000023841858,"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":0.9975000023841858,"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/T14257","display_name":"Advanced Measurement and Detection Methods","score":0.9693999886512756,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.72597736120224},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6966530680656433},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6688534021377563},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6639396548271179},{"id":"https://openalex.org/keywords/gaussian-function","display_name":"Gaussian function","score":0.5703432559967041},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.5335816144943237},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5089361667633057},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.49758532643318176},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.48076388239860535},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4511524736881256},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37657880783081055},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1496969759464264},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1496279239654541},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.1185864806175232}],"concepts":[{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.72597736120224},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6966530680656433},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6688534021377563},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6639396548271179},{"id":"https://openalex.org/C7218915","wikidata":"https://www.wikidata.org/wiki/Q1054475","display_name":"Gaussian function","level":3,"score":0.5703432559967041},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.5335816144943237},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5089361667633057},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.49758532643318176},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.48076388239860535},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4511524736881256},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37657880783081055},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1496969759464264},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1496279239654541},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.1185864806175232},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icspcc52875.2021.9564438","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icspcc52875.2021.9564438","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W1836465849","https://openalex.org/W1991141435","https://openalex.org/W2194775991","https://openalex.org/W2565639579","https://openalex.org/W2570343428","https://openalex.org/W2796347433","https://openalex.org/W2890715498","https://openalex.org/W2893926387","https://openalex.org/W2910883248","https://openalex.org/W2949117887","https://openalex.org/W2962766617","https://openalex.org/W2963351448","https://openalex.org/W2963786238","https://openalex.org/W2964241181","https://openalex.org/W2970575838","https://openalex.org/W2981958729","https://openalex.org/W2988452521","https://openalex.org/W2988916019","https://openalex.org/W3018757597","https://openalex.org/W3034971973","https://openalex.org/W4293584584","https://openalex.org/W6620707391","https://openalex.org/W6754632766"],"related_works":["https://openalex.org/W3034421924","https://openalex.org/W2982536526","https://openalex.org/W4386858688","https://openalex.org/W4380302312","https://openalex.org/W4390971171","https://openalex.org/W4385338604","https://openalex.org/W3081626085","https://openalex.org/W2375370983","https://openalex.org/W2369557298","https://openalex.org/W2545232906"],"abstract_inverted_index":{"Aiming":[0],"at":[1,144],"the":[2,6,28,36,45,48,62,73,81,100,108,111,114,129,136,145],"complex":[3],"background":[4],"of":[5,41,47,84,117],"airport":[7,14,49],"target":[8,16,85],"and":[9,71,120],"small":[10,15,50,142],"targets,":[11],"a":[12,54,67],"YOLOv3":[13,42],"detection":[17],"algorithm":[18,59,92,138],"based":[19],"on":[20],"convolution":[21,29],"kernel":[22,30],"attention":[23,31],"mechanism":[24,32],"is":[25,33,93,122,125],"proposed.":[26],"Firstly,":[27],"embedded":[34],"in":[35],"three":[37,115],"feature":[38],"fusion":[39],"layers":[40],"to":[43,60,79,103],"improve":[44,80],"score":[46],"target.":[51],"Secondly,":[52],"design":[53],"Gaussion":[55,77],"IOU(Intersection":[56],"over":[57],"Union)":[58],"obtain":[61],"JS":[63],"divergence":[64],"by":[65],"constructing":[66],"three-dimensional":[68],"Gaussian":[69,97],"function,":[70],"replace":[72],"original":[74,130],"IOU":[75,78],"with":[76],"recall":[82],"rate":[83],"detection.":[86],"Finally,":[87],"an":[88],"improved":[89],"non-maximum":[90],"suppression":[91],"proposed,":[94],"which":[95,124],"uses":[96],"function":[98],"as":[99],"attenuation":[101],"coefficient":[102],"screen":[104],"anchor":[105],"frames.":[106],"Using":[107],"designed":[109,137],"algorithm,":[110],"mAP@0.5":[112],"for":[113],"targets":[116,143],"airplanes,":[118],"cars,":[119],"people":[121],"0.951,":[123],"0.1":[126],"higher":[127],"than":[128],"YOLOv3.":[131],"The":[132],"results":[133],"show":[134],"that":[135],"can":[139],"accurately":[140],"detect":[141],"airport.":[146]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}