{"id":"https://openalex.org/W2899407520","doi":"https://doi.org/10.1109/etfa.2018.8502488","title":"Highlighted Deep Learning based Identification of Pharmaceutical Blister Packages","display_name":"Highlighted Deep Learning based Identification of Pharmaceutical Blister Packages","publication_year":2018,"publication_date":"2018-09-01","ids":{"openalex":"https://openalex.org/W2899407520","doi":"https://doi.org/10.1109/etfa.2018.8502488","mag":"2899407520"},"language":"en","primary_location":{"id":"doi:10.1109/etfa.2018.8502488","is_oa":false,"landing_page_url":"https://doi.org/10.1109/etfa.2018.8502488","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA)","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/A5071349546","display_name":"Jing Wang","orcid":"https://orcid.org/0009-0007-4115-1226"},"institutions":[{"id":"https://openalex.org/I154864474","display_name":"National Taiwan University of Science and Technology","ror":"https://ror.org/00q09pe49","country_code":"TW","type":"education","lineage":["https://openalex.org/I154864474"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Jing- Syuan Wang","raw_affiliation_strings":["Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei","institution_ids":["https://openalex.org/I154864474"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051935928","display_name":"ArulMurugan Ambikapathi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"ArulMurugan Ambikapathi","raw_affiliation_strings":["Utechzone Co. Ltd., Taipei, Taiwan"],"affiliations":[{"raw_affiliation_string":"Utechzone Co. Ltd., Taipei, Taiwan","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101445480","display_name":"Yun Han","orcid":"https://orcid.org/0000-0003-1410-8090"},"institutions":[{"id":"https://openalex.org/I4210117337","display_name":"Neijiang Normal University","ror":"https://ror.org/02bc8tz70","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210117337"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yun Han","raw_affiliation_strings":["School of Computer Sciences, Neijiang Normal University, Neijiang"],"affiliations":[{"raw_affiliation_string":"School of Computer Sciences, Neijiang Normal University, Neijiang","institution_ids":["https://openalex.org/I4210117337"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102729129","display_name":"Sheng\u2010Luen Chung","orcid":"https://orcid.org/0000-0003-0326-6448"},"institutions":[{"id":"https://openalex.org/I154864474","display_name":"National Taiwan University of Science and Technology","ror":"https://ror.org/00q09pe49","country_code":"TW","type":"education","lineage":["https://openalex.org/I154864474"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Sheng-Luen Chung","raw_affiliation_strings":["Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei","institution_ids":["https://openalex.org/I154864474"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009767964","display_name":"Hsien-Wei Ting","orcid":"https://orcid.org/0000-0003-2617-4183"},"institutions":[{"id":"https://openalex.org/I4210128529","display_name":"Taipei Hospital","ror":"https://ror.org/03c1fxf30","country_code":"TW","type":"healthcare","lineage":["https://openalex.org/I4210128529"]},{"id":"https://openalex.org/I4210119487","display_name":"Taipei City Hospital","ror":"https://ror.org/02gzfb532","country_code":"TW","type":"healthcare","lineage":["https://openalex.org/I4210119487"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Hsien-Wei Ting","raw_affiliation_strings":["Department of Neurosurgery, Taipei Hospital, New Taipei City"],"affiliations":[{"raw_affiliation_string":"Department of Neurosurgery, Taipei Hospital, New Taipei City","institution_ids":["https://openalex.org/I4210119487","https://openalex.org/I4210128529"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010175511","display_name":"Chih-Fang Chen","orcid":"https://orcid.org/0000-0002-5748-7804"},"institutions":[{"id":"https://openalex.org/I2802753785","display_name":"Mackay Memorial Hospital","ror":"https://ror.org/015b6az38","country_code":"TW","type":"healthcare","lineage":["https://openalex.org/I2802753785"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chih-Fang Chen","raw_affiliation_strings":["Department of Pharmacy, MacKay Memorial Hospital, Taipei"],"affiliations":[{"raw_affiliation_string":"Department of Pharmacy, MacKay Memorial Hospital, Taipei","institution_ids":["https://openalex.org/I2802753785"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5071349546"],"corresponding_institution_ids":["https://openalex.org/I154864474"],"apc_list":null,"apc_paid":null,"fwci":1.1705,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.77762027,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"638","last_page":"645"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12282","display_name":"Mineral Processing and Grinding","score":0.9750999808311462,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/T12282","display_name":"Mineral Processing and Grinding","score":0.9750999808311462,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/T13114","display_name":"Image Processing Techniques and Applications","score":0.97079998254776,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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":0.965399980545044,"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/computer-science","display_name":"Computer science","score":0.7108633518218994},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6952437162399292},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6333283185958862},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.582429826259613},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5156577825546265},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4223499298095703},{"id":"https://openalex.org/keywords/workstation","display_name":"Workstation","score":0.41226834058761597},{"id":"https://openalex.org/keywords/identifier","display_name":"Identifier","score":0.4113170802593231},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38872838020324707}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7108633518218994},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6952437162399292},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6333283185958862},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.582429826259613},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5156577825546265},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4223499298095703},{"id":"https://openalex.org/C67953723","wikidata":"https://www.wikidata.org/wiki/Q192525","display_name":"Workstation","level":2,"score":0.41226834058761597},{"id":"https://openalex.org/C154504017","wikidata":"https://www.wikidata.org/wiki/Q853614","display_name":"Identifier","level":2,"score":0.4113170802593231},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38872838020324707},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/etfa.2018.8502488","is_oa":false,"landing_page_url":"https://doi.org/10.1109/etfa.2018.8502488","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA)","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":21,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W1686810756","https://openalex.org/W2102605133","https://openalex.org/W2131067223","https://openalex.org/W2150341604","https://openalex.org/W2155893237","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2570343428","https://openalex.org/W2613718673","https://openalex.org/W2756120902","https://openalex.org/W2765452148","https://openalex.org/W2950094539","https://openalex.org/W2963037989","https://openalex.org/W2963420686","https://openalex.org/W3106250896","https://openalex.org/W4205947740","https://openalex.org/W6620707391","https://openalex.org/W6684191040","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W4380075502","https://openalex.org/W4223943233","https://openalex.org/W4312200629","https://openalex.org/W4360585206","https://openalex.org/W4364306694","https://openalex.org/W4380086463","https://openalex.org/W4225161397","https://openalex.org/W3014300295","https://openalex.org/W3164822677","https://openalex.org/W2795261237"],"abstract_inverted_index":{"Precise":[0],"identification":[1,73],"of":[2,25,28,35,74,123,173,188,191,242],"blister":[3,36,75,119,137,192,243],"packages":[4],"carries":[5],"utmost":[6],"importance":[7],"at":[8,167],"dispensing":[9,41,171,235],"stations,":[10],"where":[11],"numerous":[12],"prescriptions":[13],"are":[14],"to":[15,46,86,93,133,198,233],"be":[16,181,231],"efficiently":[17],"dispensed":[18],"by":[19],"pharmacists.":[20],"However,":[21],"the":[22,89,117,135,148,152,168,213,222],"usual":[23],"presence":[24],"several":[26],"hundreds":[27],"similarly":[29],"looking,":[30],"but":[31],"completely":[32],"different":[33],"types":[34,190],"packages,":[37,193,244],"in":[38,84],"a":[39,56,64],"crowded":[40],"station":[42,172,236],"makes":[43],"it":[44],"prone":[45],"human":[47],"error,":[48],"posing":[49],"serious":[50],"safety":[51],"and":[52,92,112,115,151,203,240,250],"health":[53],"concerns":[54],"for":[55,71,131,159,201,207,237],"patients":[57],"life.":[58],"In":[59],"this":[60,185],"work,":[61],"we":[62],"propose":[63],"highlighted":[65],"deep":[66,102],"learning":[67,103],"(HDL)":[68],"based":[69,104],"approach":[70,215],"accurate":[72,101],"packages.":[76],"HDL":[77,108],"allows":[78],"smart":[79],"manipulation":[80],"on":[81],"raw":[82,118],"data":[83],"order":[85],"better":[87],"segment":[88],"identified":[90],"targets":[91],"expose":[94],"inherent":[95],"descriptive":[96],"features,":[97],"thus":[98],"facilitating":[99],"an":[100,164,247],"classification":[105,241],"process.":[106],"Specifically,":[107],"uses":[109],"automatic":[110,238],"detection":[111,239],"then":[113],"segments":[114],"processes":[116],"pack":[120,138],"images":[121,196,206],"irrespective":[122],"position,":[124],"lighting":[125],"variations,":[126],"etc.,":[127],"making":[128],"them":[129],"suitable":[130],"CNN":[132,142,154],"classify":[134],"correct":[136],"types.":[139],"A":[140],"ResNet":[141],"classifier":[143],"has":[144],"been":[145],"trained":[146],"using":[147],"processed":[149],"images,":[150],"resultant":[153],"model":[155],"is":[156],"finally":[157],"deployed":[158],"classification.":[160],"We":[161],"have":[162],"conducted":[163],"extensive":[165],"experiment":[166],"adult":[169],"lozenge":[170],"MacKay":[174],"Memorial":[175],"Hospital.":[176],"The":[177,226],"database":[178],"that":[179],"will":[180],"released":[182],"along":[183],"with":[184,194],"paper,":[186],"consists":[187],"272":[189],"65":[195],"belonging":[197],"each":[199],"type":[200],"training":[202],"additional":[204],"7":[205],"validation.":[208],"On":[209],"real":[210],"testing":[211,224],"scenario,":[212],"proposed":[214,227],"yielded":[216],"almost":[217],"100%":[218],"accuracy,":[219],"consistently":[220],"over":[221],"entire":[223],"set.":[225],"solution":[228],"can":[229],"also":[230],"extended":[232],"any":[234],"thereby":[245],"offering":[246],"highly":[248],"effective":[249],"efficient":[251],"delivery":[252],"system.":[253]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
