{"id":"https://openalex.org/W4313036428","doi":"https://doi.org/10.1145/3569966.3570089","title":"A Lightweight Foreign Object Debris Detection Algorithm for Airport Runway","display_name":"A Lightweight Foreign Object Debris Detection Algorithm for Airport Runway","publication_year":2022,"publication_date":"2022-10-21","ids":{"openalex":"https://openalex.org/W4313036428","doi":"https://doi.org/10.1145/3569966.3570089"},"language":"en","primary_location":{"id":"doi:10.1145/3569966.3570089","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3569966.3570089","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 5th International Conference on Computer Science and Software Engineering","raw_type":"proceedings-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/A5008583433","display_name":"Jia-Ling Liu","orcid":"https://orcid.org/0000-0001-5356-0624"},"institutions":[{"id":"https://openalex.org/I50632499","display_name":"Chongqing University of Technology","ror":"https://ror.org/04vgbd477","country_code":"CN","type":"education","lineage":["https://openalex.org/I50632499"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jialing Liu","raw_affiliation_strings":["School of Computer Science and Engineering, Chongqing University of Technology, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Chongqing University of Technology, China","institution_ids":["https://openalex.org/I50632499"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069653714","display_name":"Yifeng Lu","orcid":"https://orcid.org/0000-0003-1973-818X"},"institutions":[{"id":"https://openalex.org/I50632499","display_name":"Chongqing University of Technology","ror":"https://ror.org/04vgbd477","country_code":"CN","type":"education","lineage":["https://openalex.org/I50632499"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yifeng Lu","raw_affiliation_strings":["School of Computer Science and Engineering, Chongqing University of Technology, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Chongqing University of Technology, China","institution_ids":["https://openalex.org/I50632499"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5008583433"],"corresponding_institution_ids":["https://openalex.org/I50632499"],"apc_list":null,"apc_paid":null,"fwci":0.4075,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.61099908,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"451","last_page":"455"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9987000226974487,"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":0.9987000226974487,"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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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":0.9878000020980835,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6966692209243774},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6750307083129883},{"id":"https://openalex.org/keywords/runway","display_name":"Runway","score":0.6113994121551514},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.606407880783081},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5591036081314087},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5485554337501526},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.526367723941803},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.49085551500320435},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4661098122596741},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4543076157569885},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.44182801246643066},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.30527061223983765},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1508619487285614},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.13508066534996033}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6966692209243774},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6750307083129883},{"id":"https://openalex.org/C81155309","wikidata":"https://www.wikidata.org/wiki/Q184590","display_name":"Runway","level":2,"score":0.6113994121551514},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.606407880783081},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5591036081314087},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5485554337501526},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.526367723941803},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.49085551500320435},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4661098122596741},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4543076157569885},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.44182801246643066},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.30527061223983765},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1508619487285614},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.13508066534996033},{"id":"https://openalex.org/C95457728","wikidata":"https://www.wikidata.org/wiki/Q309","display_name":"History","level":0,"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3569966.3570089","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3569966.3570089","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 5th International Conference on Computer Science and Software Engineering","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W1676314349","https://openalex.org/W2109255472","https://openalex.org/W2194775991","https://openalex.org/W2570343428","https://openalex.org/W2963163009","https://openalex.org/W3042011474","https://openalex.org/W6836371346"],"related_works":["https://openalex.org/W1578981866","https://openalex.org/W2373284441","https://openalex.org/W2887100346","https://openalex.org/W2056834547","https://openalex.org/W2753632835","https://openalex.org/W2102868673","https://openalex.org/W4322506511","https://openalex.org/W4362495656","https://openalex.org/W617408315","https://openalex.org/W146542191"],"abstract_inverted_index":{"Aiming":[0],"at":[1],"the":[2,15,30,34,60,71,81,85,96,106,128,143,154,164],"problem":[3],"that":[4],"small":[5],"target":[6,18,185],"detection":[7,19,43,51,186],"for":[8,188],"foreign":[9],"object":[10],"debris(FOD)":[11],"on":[12,25,49],"airport":[13],"runways,":[14],"deep":[16],"learning":[17],"algorithm":[20,44,187],"is":[21,46,57,67,124,175,181],"difficult":[22],"to":[23,29,69,94,100,126],"deploy":[24],"mobile":[26,189],"devices":[27],"due":[28],"large":[31],"size":[32],"of":[33,73,108],"model":[35,112],"and":[36,59,76,89,104,117,153,167],"too":[37],"many":[38],"parameters.":[39],"A":[40,139],"lightweight":[41],"FOD":[42],"YOLO-ACIR":[45],"proposed":[47],"based":[48],"YOLOX":[50],"model.":[52],"The":[53,172],"spatial":[54,61],"pyramid":[55,62],"structure":[56,63,88],"improved,":[58],"with":[64,136,138],"atrous":[65],"convolution":[66,91,165],"utilized":[68],"reduce":[70,105],"loss":[72,107],"local":[74],"information":[75,78],"edge":[77],"while":[79],"expanding":[80],"receptive":[82],"field.":[83],"Secondly,":[84],"inverted":[86],"residual":[87],"depth-separable":[90],"are":[92,170],"introduced":[93],"improve":[95],"feature":[97],"extraction":[98],"module":[99],"provide":[101],"richer":[102],"features":[103],"image":[109],"information.":[110],"Faster":[111],"inference":[113,156],"by":[114,149,159],"fusing":[115],"convolutional":[116],"BN":[118,168],"layers.":[119],"Finally,":[120],"FOD-A":[121],"data":[122],"set":[123],"used":[125],"verify":[127],"algorithm.":[129],"Experimental":[130],"results":[131],"show":[132],"that,":[133],"in":[134],"comparison":[135],"YOLOX-Nano":[137],"few":[140],"parameters":[141],"added,":[142],"improved":[144],"YOLO-ACIR,":[145],"[email":[146],"protected]:0.95,":[147],"increases":[148,158],"3.5":[150],"percentage":[151,161],"points,":[152],"final":[155],"speed":[157],"35.34":[160],"points":[162],"after":[163],"layer":[166,169],"fused.":[171],"comprehensive":[173],"performance":[174],"better":[176],"than":[177],"original":[178],"model,":[179],"which":[180],"a":[182],"more":[183],"suitable":[184],"devices.":[190]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}