{"id":"https://openalex.org/W4226055983","doi":"https://doi.org/10.1109/access.2022.3159102","title":"Merging Super Resolution and Attribute Learning for Low-Resolution Person Attribute Recognition","display_name":"Merging Super Resolution and Attribute Learning for Low-Resolution Person Attribute Recognition","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4226055983","doi":"https://doi.org/10.1109/access.2022.3159102"},"language":"en","primary_location":{"id":"doi:10.1109/access.2022.3159102","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3159102","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9668973/09733333.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/9668973/09733333.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5003453148","display_name":"Ramin Abbaszadi","orcid":"https://orcid.org/0000-0002-3939-9704"},"institutions":[{"id":"https://openalex.org/I66514158","display_name":"Hacettepe University","ror":"https://ror.org/04kwvgz42","country_code":"TR","type":"education","lineage":["https://openalex.org/I66514158"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Ramin Abbaszadi","raw_affiliation_strings":["Department of Computer Engineering, Hacettepe University, Ankara, Turkey"],"raw_orcid":"https://orcid.org/0000-0002-3939-9704","affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Hacettepe University, Ankara, Turkey","institution_ids":["https://openalex.org/I66514158"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090096127","display_name":"Nazl\u0131 \u0130kizler-Cinbi\u015f","orcid":"https://orcid.org/0000-0002-8644-2875"},"institutions":[{"id":"https://openalex.org/I66514158","display_name":"Hacettepe University","ror":"https://ror.org/04kwvgz42","country_code":"TR","type":"education","lineage":["https://openalex.org/I66514158"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Nazli Ikizler-Cinbis","raw_affiliation_strings":["Department of Computer Engineering, Hacettepe University, Ankara, Turkey"],"raw_orcid":"https://orcid.org/0000-0002-8644-2875","affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Hacettepe University, Ankara, Turkey","institution_ids":["https://openalex.org/I66514158"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I66514158"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.6375,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.78360049,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"10","issue":null,"first_page":"30436","last_page":"30444"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12153","display_name":"Advanced Optical Sensing Technologies","score":0.9959999918937683,"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"}},"topics":[{"id":"https://openalex.org/T12153","display_name":"Advanced Optical Sensing Technologies","score":0.9959999918937683,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.989799976348877,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9894999861717224,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8598345518112183},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.648807168006897},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5867432355880737},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.5337392091751099},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5217503309249878},{"id":"https://openalex.org/keywords/low-resolution","display_name":"Low resolution","score":0.50782710313797},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4768289625644684},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.47507089376449585},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43084716796875},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4162179231643677},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.39941924810409546},{"id":"https://openalex.org/keywords/high-resolution","display_name":"High resolution","score":0.2238081991672516}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8598345518112183},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.648807168006897},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5867432355880737},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.5337392091751099},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5217503309249878},{"id":"https://openalex.org/C3019883945","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Low resolution","level":3,"score":0.50782710313797},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4768289625644684},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.47507089376449585},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43084716796875},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4162179231643677},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39941924810409546},{"id":"https://openalex.org/C3020199158","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"High resolution","level":2,"score":0.2238081991672516},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"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/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2022.3159102","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3159102","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9668973/09733333.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:fb654dc24352476e9c40b53b4c816860","is_oa":true,"landing_page_url":"https://doaj.org/article/fb654dc24352476e9c40b53b4c816860","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 10, Pp 30436-30444 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2022.3159102","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3159102","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9668973/09733333.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Gender equality","score":0.6000000238418579,"id":"https://metadata.un.org/sdg/5"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4226055983.pdf","grobid_xml":"https://content.openalex.org/works/W4226055983.grobid-xml"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W1522973599","https://openalex.org/W1885185971","https://openalex.org/W1919542679","https://openalex.org/W1967988963","https://openalex.org/W2008144378","https://openalex.org/W2111025459","https://openalex.org/W2121058967","https://openalex.org/W2126926806","https://openalex.org/W2170057902","https://openalex.org/W2194775991","https://openalex.org/W2204750386","https://openalex.org/W2410968923","https://openalex.org/W2503339013","https://openalex.org/W2560533888","https://openalex.org/W2585635281","https://openalex.org/W2604463754","https://openalex.org/W2963372104","https://openalex.org/W2963470893","https://openalex.org/W2963620158","https://openalex.org/W2963729050","https://openalex.org/W2964971217","https://openalex.org/W2965394549","https://openalex.org/W3001992107","https://openalex.org/W3003855058","https://openalex.org/W3013799809","https://openalex.org/W3013839707","https://openalex.org/W3018839149","https://openalex.org/W3023950925","https://openalex.org/W3040726448","https://openalex.org/W3043538212","https://openalex.org/W3084521418","https://openalex.org/W3110264553","https://openalex.org/W3164382044","https://openalex.org/W6759803958","https://openalex.org/W6781412027"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W2745001401","https://openalex.org/W4321353415","https://openalex.org/W2130974462","https://openalex.org/W972276598","https://openalex.org/W4246352526","https://openalex.org/W2028665553","https://openalex.org/W2086519370","https://openalex.org/W2087343574","https://openalex.org/W2121910908"],"abstract_inverted_index":{"In":[0],"video":[1],"surveillance,":[2],"visual":[3],"person":[4,16,160],"attributes":[5,25],"such":[6],"as":[7],"gender,":[8],"backpack,":[9],"type":[10],"of":[11,31,126],"clothing":[12],"are":[13],"crucial":[14],"for":[15,112,132],"search":[17],"or":[18,48],"re-identification.":[19],"For":[20],"detecting":[21],"and":[22,81,107,124,149],"retrieving":[23],"these":[24],"with":[26],"high":[27],"accuracy,":[28],"the":[29,122,127,145],"availability":[30],"high-quality":[32],"videos":[33,47],"is":[34,60,153],"a":[35,73,82,95,137],"necessity":[36],"in":[37,44,69,158],"general.":[38],"However,":[39],"this":[40,70],"cannot":[41],"be":[42],"guaranteed":[43],"general":[45],"surveillance":[46],"images;":[49],"beside":[50],"improving":[51,54],"hardware":[52],"technology,":[53],"inference":[55],"algorithms":[56],"on":[57,88,117],"low-resolution":[58,89,133,159],"data":[59],"valuable.":[61],"This":[62],"paper":[63],"attempts":[64],"to":[65],"propose":[66],"two":[67,118],"solutions":[68],"direction:":[71],"designing":[72],"combined":[74,96],"neural":[75,129],"network":[76,130,152],"architecture":[77,93,131,148],"from":[78],"existing":[79],"architectures,":[80],"novel":[83],"combination":[84,140],"approach":[85],"toward":[86],"re-identification":[87],"videos.":[90],"The":[91],"proposed":[92,128,146],"introduces":[94],"Neural":[97],"Network":[98],"architecture,":[99],"called":[100],"SRMAR,":[101],"that":[102,142],"jointly":[103],"trains":[104],"Super":[105],"Resolution":[106],"Multi":[108],"Attribute":[109],"Recognition":[110],"models":[111],"more":[113],"effective":[114],"recognition.":[115,135,162],"Experiments":[116],"benchmark":[119],"datasets":[120],"demonstrate":[121],"effectiveness":[123],"applicability":[125],"multi-attribute":[134,150],"Furthermore,":[136],"higher-level":[138],"linear":[139],"scheme":[141],"optimally":[143],"combines":[144],"SRMAR":[147],"recognition":[151],"presented,":[154],"yielding":[155],"superior":[156],"results":[157],"attribute":[161]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}