{"id":"https://openalex.org/W4390239567","doi":"https://doi.org/10.1145/3631991.3632039","title":"Detection of Defects in Bottled Liquor Using Deep Learning","display_name":"Detection of Defects in Bottled Liquor Using Deep Learning","publication_year":2023,"publication_date":"2023-09-22","ids":{"openalex":"https://openalex.org/W4390239567","doi":"https://doi.org/10.1145/3631991.3632039"},"language":"en","primary_location":{"id":"doi:10.1145/3631991.3632039","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3631991.3632039","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 The 5th World Symposium on Software Engineering (WSSE)","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/A5041974099","display_name":"Mary Jane C. Samonte","orcid":"https://orcid.org/0000-0001-9867-8722"},"institutions":[{"id":"https://openalex.org/I137967721","display_name":"Map\u00faa University","ror":"https://ror.org/040rd2b57","country_code":"PH","type":"facility","lineage":["https://openalex.org/I137967721"]}],"countries":["PH"],"is_corresponding":true,"raw_author_name":"Mary Jane C. Samonte","raw_affiliation_strings":["Mapua University, Philippines"],"affiliations":[{"raw_affiliation_string":"Mapua University, Philippines","institution_ids":["https://openalex.org/I137967721"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090558984","display_name":"Ting Dong","orcid":"https://orcid.org/0000-0002-7873-9142"},"institutions":[{"id":"https://openalex.org/I137967721","display_name":"Map\u00faa University","ror":"https://ror.org/040rd2b57","country_code":"PH","type":"facility","lineage":["https://openalex.org/I137967721"]}],"countries":["PH"],"is_corresponding":false,"raw_author_name":"Ting Dong","raw_affiliation_strings":["Mapua University, Philippines"],"affiliations":[{"raw_affiliation_string":"Mapua University, Philippines","institution_ids":["https://openalex.org/I137967721"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016063613","display_name":"Minning Wu","orcid":"https://orcid.org/0000-0002-6676-4105"},"institutions":[{"id":"https://openalex.org/I137967721","display_name":"Map\u00faa University","ror":"https://ror.org/040rd2b57","country_code":"PH","type":"facility","lineage":["https://openalex.org/I137967721"]}],"countries":["PH"],"is_corresponding":false,"raw_author_name":"Minning Wu","raw_affiliation_strings":["Mapua University, Philippines"],"affiliations":[{"raw_affiliation_string":"Mapua University, Philippines","institution_ids":["https://openalex.org/I137967721"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073568846","display_name":"Yong Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I137967721","display_name":"Map\u00faa University","ror":"https://ror.org/040rd2b57","country_code":"PH","type":"facility","lineage":["https://openalex.org/I137967721"]}],"countries":["PH"],"is_corresponding":false,"raw_author_name":"Yong Wang","raw_affiliation_strings":["Mapua University, Philippines"],"affiliations":[{"raw_affiliation_string":"Mapua University, Philippines","institution_ids":["https://openalex.org/I137967721"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5041974099"],"corresponding_institution_ids":["https://openalex.org/I137967721"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.30429223,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"292","last_page":"297"},"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":0.9997000098228455,"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":0.9997000098228455,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.978600025177002,"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/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.9697999954223633,"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/fuse","display_name":"Fuse (electrical)","score":0.793614387512207},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.7927899956703186},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7619525194168091},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6693143844604492},{"id":"https://openalex.org/keywords/backbone-network","display_name":"Backbone network","score":0.6353667378425598},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6307039856910706},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5779674053192139},{"id":"https://openalex.org/keywords/bottle","display_name":"Bottle","score":0.5196439027786255},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5018012523651123},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4515095353126526},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4352527856826782},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12539133429527283},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0772750973701477}],"concepts":[{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.793614387512207},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.7927899956703186},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7619525194168091},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6693143844604492},{"id":"https://openalex.org/C88796919","wikidata":"https://www.wikidata.org/wiki/Q1142907","display_name":"Backbone network","level":2,"score":0.6353667378425598},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6307039856910706},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5779674053192139},{"id":"https://openalex.org/C32236832","wikidata":"https://www.wikidata.org/wiki/Q80228","display_name":"Bottle","level":2,"score":0.5196439027786255},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5018012523651123},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4515095353126526},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4352527856826782},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12539133429527283},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0772750973701477},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3631991.3632039","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3631991.3632039","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 The 5th World Symposium on Software Engineering (WSSE)","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":22,"referenced_works":["https://openalex.org/W234388709","https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W2097117768","https://openalex.org/W2100596333","https://openalex.org/W2116476901","https://openalex.org/W2152236601","https://openalex.org/W2160522381","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2549139847","https://openalex.org/W2560023338","https://openalex.org/W2565639579","https://openalex.org/W2618530766","https://openalex.org/W2746314669","https://openalex.org/W2747685395","https://openalex.org/W2911054611","https://openalex.org/W2963045696","https://openalex.org/W2990256289","https://openalex.org/W3000295996","https://openalex.org/W3019407890","https://openalex.org/W3118950806"],"related_works":["https://openalex.org/W3000097931","https://openalex.org/W2354322770","https://openalex.org/W2361630154","https://openalex.org/W4237547500","https://openalex.org/W3205445068","https://openalex.org/W3134004915","https://openalex.org/W2993564273","https://openalex.org/W4286907753","https://openalex.org/W3208389169","https://openalex.org/W3120085233"],"abstract_inverted_index":{"In":[0],"this":[1,25,126],"paper,":[2],"we":[3],"aim":[4],"at":[5],"the":[6,18,21,28,35,47,56,60,63,68,76,88,94,105,119],"problem":[7],"of":[8,20,30,44,59,79,107],"low":[9],"detection":[10,70,73,78,100,130],"accuracy":[11],"in":[12,75],"bottle":[13,22],"defect":[14,23,77],"detection;":[15],"combined":[16],"with":[17],"characteristics":[19],"dataset,":[24],"paper":[26],"adopts":[27],"method":[29,127],"data":[31],"enhancement":[32],"to":[33,37,50,83,98],"enable":[34],"model":[36],"be":[38],"trained":[39],"through":[40],"a":[41],"small":[42],"amount":[43],"information,":[45],"improve":[46,55,99,129],"model's":[48],"ability":[49,58],"capture":[51],"defects,":[52],"and":[53,71,112],"thus":[54],"generalization":[57],"model.":[61],"Secondly,":[62],"algorithm":[64],"is":[65,116],"improved":[66],"for":[67],"false":[69],"missed":[72],"problems":[74],"wine":[80],"bottles.":[81],"Due":[82],"its":[84],"unique":[85],"construction":[86],"method,":[87],"feature":[89,96,108],"pyramid":[90,109],"network":[91,110,115,121],"can":[92,128],"fuse":[93],"high-level":[95],"information":[97],"accuracy.":[101,131],"The":[102],"study":[103],"used":[104,117],"concept":[106],"(FPN)":[111],"applied":[113],"ResNet-65":[114],"as":[118],"backbone":[120],"structure.":[122],"Through":[123],"experimental":[124],"verification,":[125]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}