{"id":"https://openalex.org/W4412404529","doi":"https://doi.org/10.1109/mci.2025.3570272","title":"Quantum-Eyes: Scalable Quantum Convolutional Neural Networks for Low-Overhead Object Detection [Research Frontier]","display_name":"Quantum-Eyes: Scalable Quantum Convolutional Neural Networks for Low-Overhead Object Detection [Research Frontier]","publication_year":2025,"publication_date":"2025-07-14","ids":{"openalex":"https://openalex.org/W4412404529","doi":"https://doi.org/10.1109/mci.2025.3570272"},"language":"en","primary_location":{"id":"doi:10.1109/mci.2025.3570272","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mci.2025.3570272","pdf_url":null,"source":{"id":"https://openalex.org/S104797584","display_name":"IEEE Computational Intelligence Magazine","issn_l":"1556-603X","issn":["1556-603X","1556-6048"],"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 Computational Intelligence Magazine","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/A5049202871","display_name":"Joongheon Kim","orcid":"https://orcid.org/0000-0003-2126-768X"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Joongheon Kim","raw_affiliation_strings":["Korea University, Seoul, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Korea University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I197347611"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111208866","display_name":"Emily Jimin Roh","orcid":"https://orcid.org/0009-0008-0013-6342"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Emily Jimin Roh","raw_affiliation_strings":["Korea University, Seoul, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Korea University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I197347611"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114243483","display_name":"Chaemoon Im","orcid":"https://orcid.org/0009-0009-7270-7332"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Chaemoon Im","raw_affiliation_strings":["Korea University, Seoul, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Korea University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I197347611"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100724796","display_name":"Soohyun Park","orcid":"https://orcid.org/0000-0002-6556-9746"},"institutions":[{"id":"https://openalex.org/I31766871","display_name":"Sookmyung Women's University","ror":"https://ror.org/00vvvt117","country_code":"KR","type":"education","lineage":["https://openalex.org/I31766871"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Soohyun Park","raw_affiliation_strings":["Sookmyung Women&#x2019;s University, Seoul, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Sookmyung Women&#x2019;s University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I31766871"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5049202871"],"corresponding_institution_ids":["https://openalex.org/I197347611"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.15110044,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"20","issue":"3","first_page":"63","last_page":"74"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9878000020980835,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9878000020980835,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T12153","display_name":"Advanced Optical Sensing Technologies","score":0.9854000210762024,"subfield":{"id":"https://openalex.org/subfields/3105","display_name":"Instrumentation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11324","display_name":"Spectroscopy Techniques in Biomedical and Chemical Research","score":0.9843000173568726,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7513991594314575},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6780821681022644},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6097379326820374},{"id":"https://openalex.org/keywords/quantum","display_name":"Quantum","score":0.6096600890159607},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.5858989357948303},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5435795783996582},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42528143525123596},{"id":"https://openalex.org/keywords/frontier","display_name":"Frontier","score":0.4217492938041687},{"id":"https://openalex.org/keywords/quantum-computer","display_name":"Quantum computer","score":0.4212718605995178},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3552345335483551},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.14160707592964172},{"id":"https://openalex.org/keywords/quantum-mechanics","display_name":"Quantum mechanics","score":0.07920482754707336}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7513991594314575},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6780821681022644},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6097379326820374},{"id":"https://openalex.org/C84114770","wikidata":"https://www.wikidata.org/wiki/Q46344","display_name":"Quantum","level":2,"score":0.6096600890159607},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.5858989357948303},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5435795783996582},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42528143525123596},{"id":"https://openalex.org/C2778571376","wikidata":"https://www.wikidata.org/wiki/Q1355821","display_name":"Frontier","level":2,"score":0.4217492938041687},{"id":"https://openalex.org/C58053490","wikidata":"https://www.wikidata.org/wiki/Q176555","display_name":"Quantum computer","level":3,"score":0.4212718605995178},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3552345335483551},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.14160707592964172},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.07920482754707336},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C95457728","wikidata":"https://www.wikidata.org/wiki/Q309","display_name":"History","level":0,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mci.2025.3570272","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mci.2025.3570272","pdf_url":null,"source":{"id":"https://openalex.org/S104797584","display_name":"IEEE Computational Intelligence Magazine","issn_l":"1556-603X","issn":["1556-603X","1556-6048"],"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 Computational Intelligence Magazine","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W2115579991","https://openalex.org/W2148933577","https://openalex.org/W2186094539","https://openalex.org/W2954939433","https://openalex.org/W2989603244","https://openalex.org/W3009313620","https://openalex.org/W3027746348","https://openalex.org/W3098599423","https://openalex.org/W3125913056","https://openalex.org/W3173370496","https://openalex.org/W3186461170","https://openalex.org/W3209612530","https://openalex.org/W4281257218","https://openalex.org/W4287112974","https://openalex.org/W4289606390","https://openalex.org/W4312694312","https://openalex.org/W4382364303","https://openalex.org/W4386144970","https://openalex.org/W4402915329","https://openalex.org/W4407064753","https://openalex.org/W6686583229","https://openalex.org/W6755964158","https://openalex.org/W6846668058"],"related_works":["https://openalex.org/W2347401120","https://openalex.org/W2041961361","https://openalex.org/W2310010941","https://openalex.org/W1988132375","https://openalex.org/W2334292868","https://openalex.org/W579144800","https://openalex.org/W2147233680","https://openalex.org/W2069525434","https://openalex.org/W2969228573","https://openalex.org/W2963690996"],"abstract_inverted_index":{"Quantum":[0],"neural":[1,45],"networks":[2],"(QNNs)":[3],"are":[4],"gaining":[5],"attention":[6],"as":[7,32],"a":[8,42,85,101],"promising":[9],"foundation":[10],"for":[11,52],"next-generation":[12],"machine":[13,121],"learning.":[14,122],"However,":[15],"the":[16,53,91,96,116,127,132],"practical":[17],"deployment":[18],"of":[19,88,98,118,131],"QNNs,":[20],"particularly":[21],"in":[22],"vision":[23,145],"tasks,":[24],"remains":[25],"limited":[26,86],"due":[27],"to":[28,78,107,143],"hardware":[29,150],"constraints":[30],"such":[31],"qubit":[33],"scarcity.":[34],"To":[35],"address":[36],"this":[37,39],"challenge,":[38],"paper":[40],"proposes":[41],"quantum":[43,57,109,120,134,149],"convolutional":[44],"network":[46,105],"(QCNN)-based":[47],"object":[48,82,135],"detection":[49,83,113,136],"framework":[50],"designed":[51],"noisy":[54],"intermediate":[55],"scale":[56],"(NISQ)":[58],"era.":[59],"The":[60,123],"proposed":[61,133],"method":[62],"introduces":[63],"four":[64],"key":[65],"components,":[66],"patch":[67],"processing,":[68],"channel":[69,72],"uploading,":[70],"hybrid":[71],"construction,":[73],"and":[74,129],"heterogeneous":[75],"knowledge":[76,92,99],"distillation,":[77],"enable":[79],"efficient":[80],"multi-channel":[81],"with":[84],"number":[87],"qubits.":[89],"Furthermore,":[90],"distillation":[93],"strategy":[94],"facilitates":[95],"transfer":[97],"from":[100],"classical":[102],"region":[103],"proposal":[104],"(RPN)":[106],"its":[108],"counterpart,":[110],"thereby":[111],"enhancing":[112],"accuracy":[114],"despite":[115],"limitations":[117],"early-stage":[119],"evaluation":[124],"results":[125],"demonstrate":[126],"feasibility":[128],"efficiency":[130],"model,":[137],"which":[138],"can":[139],"be":[140],"effectively":[141],"applied":[142],"complex":[144],"tasks":[146],"within":[147],"existing":[148],"limitations.":[151]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
