{"id":"https://openalex.org/W3215704829","doi":"https://doi.org/10.1109/rose52750.2021.9611773","title":"Recycling of printed circuit boards by robot manipulator: A Deep Learning Approach","display_name":"Recycling of printed circuit boards by robot manipulator: A Deep Learning Approach","publication_year":2021,"publication_date":"2021-10-28","ids":{"openalex":"https://openalex.org/W3215704829","doi":"https://doi.org/10.1109/rose52750.2021.9611773","mag":"3215704829"},"language":"en","primary_location":{"id":"doi:10.1109/rose52750.2021.9611773","is_oa":false,"landing_page_url":"https://doi.org/10.1109/rose52750.2021.9611773","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Symposium on Robotic and Sensors Environments (ROSE)","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/A5113975432","display_name":"Kohei Naito","orcid":null},"institutions":[{"id":"https://openalex.org/I204291657","display_name":"Hosei University","ror":"https://ror.org/00bx6dj65","country_code":"JP","type":"education","lineage":["https://openalex.org/I204291657"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Kohei Naito","raw_affiliation_strings":["Graduate School of Science and Engineering, Hosei University, Koganei-shi, Tokyo, JAPAN"],"affiliations":[{"raw_affiliation_string":"Graduate School of Science and Engineering, Hosei University, Koganei-shi, Tokyo, JAPAN","institution_ids":["https://openalex.org/I204291657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048644831","display_name":"Aya Shirai","orcid":null},"institutions":[{"id":"https://openalex.org/I204291657","display_name":"Hosei University","ror":"https://ror.org/00bx6dj65","country_code":"JP","type":"education","lineage":["https://openalex.org/I204291657"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Aya Shirai","raw_affiliation_strings":["Graduate School of Science and Engineering, Hosei University, Koganei-shi, Tokyo, JAPAN"],"affiliations":[{"raw_affiliation_string":"Graduate School of Science and Engineering, Hosei University, Koganei-shi, Tokyo, JAPAN","institution_ids":["https://openalex.org/I204291657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112237590","display_name":"Shin-ichiro Kaneko","orcid":null},"institutions":[{"id":"https://openalex.org/I2802083021","display_name":"Toyama College","ror":"https://ror.org/01w6k3w63","country_code":"JP","type":"education","lineage":["https://openalex.org/I2802083021"]},{"id":"https://openalex.org/I10520737","display_name":"National Institute of Technology, Toyama College","ror":"https://ror.org/04jvka613","country_code":"JP","type":"education","lineage":["https://openalex.org/I10520737","https://openalex.org/I4210120810"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shin-ichiro Kaneko","raw_affiliation_strings":["National Institute of Technology, Toyama College, Toyama, Japan"],"affiliations":[{"raw_affiliation_string":"National Institute of Technology, Toyama College, Toyama, Japan","institution_ids":["https://openalex.org/I2802083021","https://openalex.org/I10520737"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002360849","display_name":"Genci Capi","orcid":"https://orcid.org/0000-0003-2079-9959"},"institutions":[{"id":"https://openalex.org/I204291657","display_name":"Hosei University","ror":"https://ror.org/00bx6dj65","country_code":"JP","type":"education","lineage":["https://openalex.org/I204291657"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Genci Capi","raw_affiliation_strings":["Graduate School of Science and Engineering, Hosei University, Koganei-shi, Tokyo, JAPAN"],"affiliations":[{"raw_affiliation_string":"Graduate School of Science and Engineering, Hosei University, Koganei-shi, Tokyo, JAPAN","institution_ids":["https://openalex.org/I204291657"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5113975432"],"corresponding_institution_ids":["https://openalex.org/I204291657"],"apc_list":null,"apc_paid":null,"fwci":0.412,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.62330752,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"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/T10653","display_name":"Robot Manipulation and Learning","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10653","display_name":"Robot Manipulation and Learning","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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":0.9911999702453613,"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/T11814","display_name":"Advanced Manufacturing and Logistics Optimization","score":0.98580002784729,"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/printed-circuit-board","display_name":"Printed circuit board","score":0.8451638221740723},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.7398675680160522},{"id":"https://openalex.org/keywords/smt-placement-equipment","display_name":"SMT placement equipment","score":0.7245880961418152},{"id":"https://openalex.org/keywords/electronic-component","display_name":"Electronic component","score":0.6825330257415771},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.6033123135566711},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5786632299423218},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5282962322235107},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.46440553665161133},{"id":"https://openalex.org/keywords/manipulator","display_name":"Manipulator (device)","score":0.4573901891708374},{"id":"https://openalex.org/keywords/electronics","display_name":"Electronics","score":0.4496501088142395},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44569703936576843},{"id":"https://openalex.org/keywords/reuse","display_name":"Reuse","score":0.442058265209198},{"id":"https://openalex.org/keywords/electronic-waste","display_name":"Electronic waste","score":0.4218648672103882},{"id":"https://openalex.org/keywords/mobile-robot","display_name":"Mobile robot","score":0.41256392002105713},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.39422762393951416},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.28716930747032166},{"id":"https://openalex.org/keywords/mechanical-engineering","display_name":"Mechanical engineering","score":0.21171939373016357},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.14417529106140137},{"id":"https://openalex.org/keywords/waste-management","display_name":"Waste management","score":0.10943835973739624},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.09652695059776306}],"concepts":[{"id":"https://openalex.org/C120793396","wikidata":"https://www.wikidata.org/wiki/Q173350","display_name":"Printed circuit board","level":2,"score":0.8451638221740723},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.7398675680160522},{"id":"https://openalex.org/C17511633","wikidata":"https://www.wikidata.org/wiki/Q830694","display_name":"SMT placement equipment","level":3,"score":0.7245880961418152},{"id":"https://openalex.org/C81060104","wikidata":"https://www.wikidata.org/wiki/Q11653","display_name":"Electronic component","level":2,"score":0.6825330257415771},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.6033123135566711},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5786632299423218},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5282962322235107},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.46440553665161133},{"id":"https://openalex.org/C2781347998","wikidata":"https://www.wikidata.org/wiki/Q1587588","display_name":"Manipulator (device)","level":3,"score":0.4573901891708374},{"id":"https://openalex.org/C138331895","wikidata":"https://www.wikidata.org/wiki/Q11650","display_name":"Electronics","level":2,"score":0.4496501088142395},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44569703936576843},{"id":"https://openalex.org/C206588197","wikidata":"https://www.wikidata.org/wiki/Q846574","display_name":"Reuse","level":2,"score":0.442058265209198},{"id":"https://openalex.org/C2775930972","wikidata":"https://www.wikidata.org/wiki/Q327400","display_name":"Electronic waste","level":2,"score":0.4218648672103882},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.41256392002105713},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.39422762393951416},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.28716930747032166},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.21171939373016357},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.14417529106140137},{"id":"https://openalex.org/C548081761","wikidata":"https://www.wikidata.org/wiki/Q180388","display_name":"Waste management","level":1,"score":0.10943835973739624},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.09652695059776306},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/rose52750.2021.9611773","is_oa":false,"landing_page_url":"https://doi.org/10.1109/rose52750.2021.9611773","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Symposium on Robotic and Sensors Environments (ROSE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.4000000059604645,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W173014460","https://openalex.org/W1602010302","https://openalex.org/W1692644283","https://openalex.org/W1999156278","https://openalex.org/W2032495001","https://openalex.org/W2039387318","https://openalex.org/W2136922672","https://openalex.org/W2149611759","https://openalex.org/W2161893161","https://openalex.org/W2407369443","https://openalex.org/W2581260460","https://openalex.org/W2582386391","https://openalex.org/W2618865658","https://openalex.org/W6681916653","https://openalex.org/W6683819664","https://openalex.org/W6713912449"],"related_works":["https://openalex.org/W2153060608","https://openalex.org/W2188146187","https://openalex.org/W4372294755","https://openalex.org/W2379772394","https://openalex.org/W2036494154","https://openalex.org/W16482907","https://openalex.org/W4312100855","https://openalex.org/W2364791190","https://openalex.org/W3135784728","https://openalex.org/W2009175695"],"abstract_inverted_index":{"Electronic":[0],"circuit":[1],"boards":[2,108],"in":[3,14,94,124,129,164,188],"mobile":[4],"phones,":[5],"PCs,":[6],"home":[7],"appliances,":[8],"etc.":[9],"that":[10,31],"are":[11,28,87,122,186],"no":[12],"longer":[13],"use":[15],"contain":[16],"many":[17],"useful":[18],"parts":[19,185],"such":[20,58],"as":[21,59],"resin":[22],"and":[23,61,69,85,112,138,154,172,182,197],"metals.":[24],"In":[25,76,97,117,157,191],"addition,":[26,77,192],"there":[27],"toxic":[29],"elements":[30],"need":[32],"a":[33,73,92,102,130],"specific":[34],"treatment.":[35],"Japan":[36],"now":[37],"depends":[38],"almost":[39],"entirely":[40],"on":[41,168],"foreign":[42],"countries":[43],"for":[44,104,202],"the":[45,120,140,162,169,173,176,183,195,200],"required":[46,81],"metal":[47],"resources.":[48],"Since":[49],"most":[50],"electronic":[51,115],"waste":[52],"is":[53,64,80,91,180],"composed":[54],"of":[55,106,114,142,199,205],"complex":[56],"materials":[57],"plastics":[60],"metals,":[62],"it":[63],"difficult":[65],"to":[66,72,82],"isolate":[67],"them":[68,71],"return":[70],"single":[74],"resource.":[75],"dedicated":[78],"equipment":[79],"recover":[83],"resources,":[84],"sensors":[86],"often":[88],"used,":[89],"which":[90,127],"factor":[93],"increasing":[95],"costs.":[96],"this":[98],"paper":[99],"we":[100,136,160,193],"develop":[101],"system":[103],"recycling":[105],"PCB":[107,152],"through":[109],"classification,":[110],"recovery":[111],"management":[113],"parts.":[116],"our":[118,158],"method,":[119],"PCBs":[121,206],"divided":[123],"small":[125],"pieces":[126],"moves":[128],"belt":[131],"conveyer.":[132],"For":[133],"component":[134,153],"recognition,":[135],"trained":[137],"compared":[139],"performance":[141],"two":[143],"Convolution":[144],"Neural":[145],"Networks":[146],"(CNN).":[147],"The":[148],"camera":[149,170],"detects":[150],"each":[151],"classify":[155],"it.":[156],"implementation":[159],"classified":[161,184],"components":[163],"five":[165],"classes.":[166],"Based":[167],"information":[171],"conveyer":[174],"speed":[175],"robot":[177],"manipulator":[178],"motion":[179],"generated":[181],"sorted":[187],"separate":[189],"containers.":[190],"investigated":[194],"shape":[196],"material":[198],"gripper":[201],"easy":[203],"grasping":[204],"components.":[207]},"counts_by_year":[{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}