{"id":"https://openalex.org/W4409059796","doi":"https://doi.org/10.1109/tii.2025.3545046","title":"Enhancing Automated Vending Machine Product Recognition Through Depth-Guided Regression Refinement","display_name":"Enhancing Automated Vending Machine Product Recognition Through Depth-Guided Regression Refinement","publication_year":2025,"publication_date":"2025-04-01","ids":{"openalex":"https://openalex.org/W4409059796","doi":"https://doi.org/10.1109/tii.2025.3545046"},"language":"en","primary_location":{"id":"doi:10.1109/tii.2025.3545046","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2025.3545046","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Industrial Informatics","raw_type":"journal-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/A5113511710","display_name":"Jinjin Qian","orcid":"https://orcid.org/0009-0002-9774-493X"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinjin Qian","raw_affiliation_strings":["School of Software Engineering, Xi'an Jiaotong University, Xi'an, China"],"raw_orcid":"https://orcid.org/0009-0002-9774-493X","affiliations":[{"raw_affiliation_string":"School of Software Engineering, Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019927202","display_name":"Chengxu Liu","orcid":"https://orcid.org/0000-0001-8023-9465"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengxu Liu","raw_affiliation_strings":["School of Information and Communication Engineering, Xi'an Jiaotong University, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0001-8023-9465","affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5116143806","display_name":"Yubin Ai","orcid":null},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yubin Ai","raw_affiliation_strings":["School of Software Engineering, Xi'an Jiaotong University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Software Engineering, Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079805574","display_name":"Guoshuai Zhao","orcid":"https://orcid.org/0000-0003-4392-8450"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoshuai Zhao","raw_affiliation_strings":["School of Software Engineering, Xi'an Jiaotong University, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0003-4392-8450","affiliations":[{"raw_affiliation_string":"School of Software Engineering, Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014825654","display_name":"Xueming Qian","orcid":"https://orcid.org/0000-0002-3173-6307"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xueming Qian","raw_affiliation_strings":["School of Information and Communication Engineering, Xi'an Jiaotong University, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0002-3173-6307","affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I87445476"],"apc_list":null,"apc_paid":null,"fwci":0.5842,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.65667129,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"21","issue":"6","first_page":"4565","last_page":"4575"},"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":0.946399986743927,"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":0.946399986743927,"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/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.9003999829292297,"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":0.626561164855957},{"id":"https://openalex.org/keywords/product","display_name":"Product (mathematics)","score":0.5485986471176147},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47345679998397827},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.424945592880249},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.423193097114563},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38498643040657043},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3644068241119385},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3485901355743408},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2271495759487152},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16694501042366028}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.626561164855957},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.5485986471176147},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47345679998397827},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.424945592880249},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.423193097114563},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38498643040657043},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3644068241119385},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3485901355743408},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2271495759487152},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16694501042366028},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tii.2025.3545046","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2025.3545046","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Industrial Informatics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4699999988079071,"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth"}],"awards":[{"id":"https://openalex.org/G1070160424","display_name":null,"funder_award_id":"62103317","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3353997047","display_name":null,"funder_award_id":"2020M683496","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G461447795","display_name":null,"funder_award_id":"62372364","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8157936946","display_name":null,"funder_award_id":"62272380","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation 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/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W2565639579","https://openalex.org/W2592299985","https://openalex.org/W2955639361","https://openalex.org/W2962766617","https://openalex.org/W2962858109","https://openalex.org/W2963351448","https://openalex.org/W2964241181","https://openalex.org/W2971900262","https://openalex.org/W2974766322","https://openalex.org/W2980340092","https://openalex.org/W2989604896","https://openalex.org/W2989608398","https://openalex.org/W2991093009","https://openalex.org/W3012573144","https://openalex.org/W3034993937","https://openalex.org/W3035180028","https://openalex.org/W3035396860","https://openalex.org/W3046768359","https://openalex.org/W3096609285","https://openalex.org/W3118453581","https://openalex.org/W3157439125","https://openalex.org/W3203040502","https://openalex.org/W4214507171","https://openalex.org/W4214630662","https://openalex.org/W4225745741","https://openalex.org/W4283733772","https://openalex.org/W4289752563","https://openalex.org/W4307176630","https://openalex.org/W4313561335","https://openalex.org/W4324125683","https://openalex.org/W4386075854","https://openalex.org/W4386076325","https://openalex.org/W4386634538","https://openalex.org/W4389776880","https://openalex.org/W4390873008","https://openalex.org/W4390873750","https://openalex.org/W4393158893","https://openalex.org/W4398756379","https://openalex.org/W4399938885","https://openalex.org/W4404722284","https://openalex.org/W6750227808","https://openalex.org/W6784094891","https://openalex.org/W6847207718"],"related_works":["https://openalex.org/W31220157","https://openalex.org/W2312753042","https://openalex.org/W4289356671","https://openalex.org/W2389155397","https://openalex.org/W2165884543","https://openalex.org/W3186837933","https://openalex.org/W2368989808","https://openalex.org/W1969346022","https://openalex.org/W2034959125","https://openalex.org/W2355687852"],"abstract_inverted_index":{"Deep":[0],"neural":[1],"network":[2,98],"advancements":[3],"have":[4],"led":[5],"to":[6,51,143],"significant":[7],"progress":[8],"in":[9,13,48,74],"industrial":[10],"applications,":[11],"particularly":[12],"product":[14,53,85,187],"recognition":[15,54,86,188],"for":[16,59,115,162],"smart":[17],"automated":[18],"vending":[19],"machines":[20],"(AVMs).":[21],"This":[22],"area":[23],"has":[24],"seen":[25],"increased":[26],"market":[27],"demand":[28],"as":[29],"a":[30,83,94,101,207,214,225],"fundamental":[31],"part":[32],"of":[33,66,90,211],"automatedretail.":[34],"However,":[35],"the":[36,64,127,130,138,167,185,195,203,218],"existing":[37,168],"works":[38],"possess":[39],"critical":[40],"gaps:":[41],"1)":[42],"densely":[43],"placed":[44],"and":[45,100,123,151,190,223],"obscured":[46],"objects":[47],"AVMs":[49],"lead":[50],"inaccurate":[52,186],"results,":[55],"necessitating":[56],"auxiliary":[57,69],"information":[58,70,135,155,161],"achieving":[60],"precise":[61],"detection;":[62],"2)":[63],"lack":[65],"datasets":[67],"with":[68],"hinders":[71],"further":[72],"development":[73],"this":[75],"field.":[76],"To":[77],"address":[78],"these":[79],"gaps,":[80],"we":[81,147],"propose":[82],"depth-guided":[84],"network,":[87],"which":[88,158],"consists":[89],"two":[91],"novel":[92],"components:":[93],"depth-aware":[95,102],"feature":[96],"pyramid":[97],"(DFPN)":[99],"regression":[103,116,131],"head":[104],"(DRH).":[105],"Our":[106],"DFPN":[107],"can":[108],"adaptively":[109],"select":[110],"features":[111],"that":[112,180],"are":[113],"beneficial":[114],"from":[117],"both":[118],"red,":[119],"green,":[120],"blue":[121],"(RGB)":[122],"depth":[124,134,154,160],"data,":[125],"whereas":[126],"DRH":[128],"refines":[129],"branch":[132],"via":[133],"without":[136],"affecting":[137],"classification":[139],"process.":[140],"In":[141],"addition,":[142],"overcome":[144],"dataset":[145,156],"limitations,":[146],"develop":[148],"an":[149],"extended":[150],"fully":[152],"annotated":[153],"namedSmartUVM-D,":[157],"includes":[159],"each":[163],"image":[164],"based":[165],"on":[166,175,202],"SmartUVM":[169],"dataset.":[170],"The":[171],"experimental":[172],"results":[173],"obtained":[174],"our":[176,181,199],"SmartUVM-D":[177],"benchmark":[178],"show":[179],"method":[182,200,222],"effectively":[183],"solves":[184],"problem":[189],"achieves":[191,206],"substantial":[192],"gains":[193],"over":[194,217],"baseline":[196],"approaches.":[197],"Specifically,":[198],"(based":[201],"ATSS":[204,221],"framework)":[205],"mean":[208],"average":[209],"precision":[210],"84.4,":[212],"representing":[213],"2.3-point":[215],"improvement":[216],"previously":[219],"developed":[220],"establishing":[224],"new":[226],"state-of-the-art":[227],"approach.":[228]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}