{"id":"https://openalex.org/W3118950806","doi":"https://doi.org/10.1109/icarcv50220.2020.9305489","title":"An Efficient and Light-weight Detector for Wine Bottle Defects","display_name":"An Efficient and Light-weight Detector for Wine Bottle Defects","publication_year":2020,"publication_date":"2020-12-13","ids":{"openalex":"https://openalex.org/W3118950806","doi":"https://doi.org/10.1109/icarcv50220.2020.9305489","mag":"3118950806"},"language":"en","primary_location":{"id":"doi:10.1109/icarcv50220.2020.9305489","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icarcv50220.2020.9305489","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 16th International Conference on Control, Automation, Robotics and Vision (ICARCV)","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/A5057710297","display_name":"Mingyuan Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingyuan Lin","raw_affiliation_strings":["Zhejiang University, Hangzhou, CO, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, CO, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101699384","display_name":"Longhua Ma","orcid":"https://orcid.org/0000-0001-7802-0675"},"institutions":[{"id":"https://openalex.org/I159389169","display_name":"Ningbo University of Technology","ror":"https://ror.org/037dym702","country_code":"CN","type":"education","lineage":["https://openalex.org/I159389169"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Longhua Ma","raw_affiliation_strings":["College of Information Science and Engineering, Ningbo Tech University, Ningbo, CO, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Ningbo Tech University, Ningbo, CO, China","institution_ids":["https://openalex.org/I159389169"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091763433","display_name":"Binchao Yu","orcid":"https://orcid.org/0000-0003-0664-2971"},"institutions":[{"id":"https://openalex.org/I4210119683","display_name":"Zhejiang Water Conservancy and Hydropower Survey and Design Institute","ror":"https://ror.org/02n6dhr29","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210119683"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Binchao Yu","raw_affiliation_strings":["Technical quality Department of Zhejiang Zheneng Natural Gas Operation Co,Hangzhou,CO,China,315100"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technical quality Department of Zhejiang Zheneng Natural Gas Operation Co,Hangzhou,CO,China,315100","institution_ids":["https://openalex.org/I4210119683"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5423,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.75362227,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"957","last_page":"962"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9987000226974487,"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"}},"topics":[{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9987000226974487,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9842000007629395,"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/T10616","display_name":"Smart Agriculture and AI","score":0.9811999797821045,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/bottle","display_name":"Bottle","score":0.8972808122634888},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.8454240560531616},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.6429632902145386},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5776417255401611},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4815855026245117},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.4597068428993225},{"id":"https://openalex.org/keywords/wine","display_name":"Wine","score":0.45524969696998596},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.45118433237075806},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.3745458126068115},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.3255974054336548},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.12400752305984497},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.07983320951461792}],"concepts":[{"id":"https://openalex.org/C32236832","wikidata":"https://www.wikidata.org/wiki/Q80228","display_name":"Bottle","level":2,"score":0.8972808122634888},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.8454240560531616},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.6429632902145386},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5776417255401611},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4815855026245117},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.4597068428993225},{"id":"https://openalex.org/C55952523","wikidata":"https://www.wikidata.org/wiki/Q3014419","display_name":"Wine","level":2,"score":0.45524969696998596},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.45118433237075806},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.3745458126068115},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.3255974054336548},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.12400752305984497},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.07983320951461792},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","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/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icarcv50220.2020.9305489","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icarcv50220.2020.9305489","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 16th International Conference on Control, Automation, Robotics and Vision (ICARCV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3856905517","display_name":null,"funder_award_id":"61633019","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4945292013","display_name":null,"funder_award_id":"2018YFB1702200","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W1686810756","https://openalex.org/W2031489346","https://openalex.org/W2097117768","https://openalex.org/W2102605133","https://openalex.org/W2117539524","https://openalex.org/W2163605009","https://openalex.org/W2193145675","https://openalex.org/W2194775991","https://openalex.org/W2279098554","https://openalex.org/W2531409750","https://openalex.org/W2553303224","https://openalex.org/W2565639579","https://openalex.org/W2570343428","https://openalex.org/W2612445135","https://openalex.org/W2796347433","https://openalex.org/W2883780447","https://openalex.org/W2884561390","https://openalex.org/W2899771611","https://openalex.org/W2905374808","https://openalex.org/W2955425717","https://openalex.org/W2962835968","https://openalex.org/W2962851801","https://openalex.org/W2963037989","https://openalex.org/W2963125010","https://openalex.org/W2963163009","https://openalex.org/W2963346150","https://openalex.org/W2963420686","https://openalex.org/W2964241181","https://openalex.org/W2973095754","https://openalex.org/W2982083293","https://openalex.org/W3018757597","https://openalex.org/W3103461182","https://openalex.org/W3106250896","https://openalex.org/W4293584584","https://openalex.org/W4297775537","https://openalex.org/W6637373629","https://openalex.org/W6684191040","https://openalex.org/W6762718338"],"related_works":["https://openalex.org/W2361630154","https://openalex.org/W2363759231","https://openalex.org/W2379779042","https://openalex.org/W2182302923","https://openalex.org/W2056206426","https://openalex.org/W118488366","https://openalex.org/W2159176067","https://openalex.org/W2616562541","https://openalex.org/W2132121638","https://openalex.org/W2064058750"],"abstract_inverted_index":{"Detecting":[0],"defects":[1,17,24],"on":[2,18,28,95],"the":[3,19,49,60,63,69,87,96,103,121],"wine":[4],"bottle":[5,33],"surface":[6],"is":[7],"a":[8,82,91,128],"challenging":[9],"task":[10],"due":[11],"to":[12,80,102],"these":[13],"factors:":[14],"(1)":[15],"tiny":[16],"surface,":[20,34],"(2)":[21],"visually":[22],"similar":[23,99],"with":[25],"design":[26],"patterns":[27],"bottles,":[29],"(3)":[30],"reflective":[31],"(metallic)":[32],"(4)":[35],"real-time":[36],"requirement.":[37],"In":[38,72,86],"this":[39,52],"paper,":[40],"we":[41,54,74,89],"propose":[42],"an":[43],"efficient":[44],"and":[45,65,133],"light-weight":[46],"detector":[47,64,110,126],"for":[48],"defects.":[50],"To":[51],"end,":[53],"adopt":[55],"EfficientNet-":[56],"B3":[57],"[1]":[58],"as":[59,68],"backbone":[61],"of":[62,93,108,120],"YOLO":[66],"[2]":[67],"detection":[70],"head.":[71],"addition,":[73],"use":[75],"channel":[76],"pruning":[77],"approach":[78],"[3]":[79],"obtain":[81,90],"more":[83],"compact":[84],"model.":[85],"experiments,":[88],"score":[92],"0.77":[94],"validation":[97],"dataset,":[98],"performance":[100],"comparing":[101],"two-stage":[104],"methods[23].":[105],"The":[106,124],"parameters":[107],"our":[109],"are":[111,116],"only":[112],"5.":[113],"8M,":[114],"which":[115],"about":[117],"one":[118],"tenth":[119],"YOLO's":[122],"[2].":[123],"proposed":[125],"achieves":[127],"good":[129],"balance":[130],"between":[131],"speed":[132],"accuracy.":[134]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2023,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
