{"id":"https://openalex.org/W2767836774","doi":"https://doi.org/10.1109/msp.2017.2736018","title":"Deep Convolutional Neural Models for Picture-Quality Prediction: Challenges and Solutions to Data-Driven Image Quality Assessment","display_name":"Deep Convolutional Neural Models for Picture-Quality Prediction: Challenges and Solutions to Data-Driven Image Quality Assessment","publication_year":2017,"publication_date":"2017-11-01","ids":{"openalex":"https://openalex.org/W2767836774","doi":"https://doi.org/10.1109/msp.2017.2736018","mag":"2767836774"},"language":"en","primary_location":{"id":"doi:10.1109/msp.2017.2736018","is_oa":false,"landing_page_url":"https://doi.org/10.1109/msp.2017.2736018","pdf_url":null,"source":{"id":"https://openalex.org/S120977877","display_name":"IEEE Signal Processing Magazine","issn_l":"1053-5888","issn":["1053-5888","1558-0792"],"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 Signal Processing 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/A5102916130","display_name":"Jongyoo Kim","orcid":"https://orcid.org/0000-0002-2435-9195"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jongyoo Kim","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, Yonsei University, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, Yonsei University, South Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012799900","display_name":"Hui Zeng","orcid":"https://orcid.org/0000-0001-6862-6964"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Hui Zeng","raw_affiliation_strings":["Department of Computing, The Hong Kong Polytechnic University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computing, The Hong Kong Polytechnic University","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034260819","display_name":"Deepti Ghadiyaram","orcid":"https://orcid.org/0000-0002-0736-0602"},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Deepti Ghadiyaram","raw_affiliation_strings":["Department of Computer Science, University of Texas (UT), Austin"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Texas (UT), Austin","institution_ids":["https://openalex.org/I86519309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100320181","display_name":"Sanghoon Lee","orcid":"https://orcid.org/0000-0001-9895-5347"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sanghoon Lee","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, Yonsei University, South Korea"],"raw_orcid":"https://orcid.org/0000-0001-9895-5347","affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, Yonsei University, South Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100433899","display_name":"Lei Zhang","orcid":"https://orcid.org/0000-0002-2078-4215"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Lei Zhang","raw_affiliation_strings":["Department of Computing, The Hong Kong Polytechnic University"],"raw_orcid":"https://orcid.org/0000-0002-2078-4215","affiliations":[{"raw_affiliation_string":"Department of Computing, The Hong Kong Polytechnic University","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075463806","display_name":"Alan C. Bovik","orcid":"https://orcid.org/0000-0001-6067-710X"},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alan C. Bovik","raw_affiliation_strings":["University of Texas, Austin"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Texas, Austin","institution_ids":["https://openalex.org/I86519309"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":12.2855,"has_fulltext":false,"cited_by_count":287,"citation_normalized_percentile":{"value":0.99026344,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"34","issue":"6","first_page":"130","last_page":"141"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":0.9998999834060669,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9961000084877014,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9955999851226807,"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/convolutional-neural-network","display_name":"Convolutional neural network","score":0.8528544902801514},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8247874975204468},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6678853034973145},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.6499581933021545},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6276655197143555},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.6235239505767822},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6078684329986572},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5987356901168823},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.5672901272773743},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.48122477531433105},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.46816039085388184},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.44552505016326904},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.4363164007663727},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.43234843015670776},{"id":"https://openalex.org/keywords/data-quality","display_name":"Data quality","score":0.4316667914390564},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4223855137825012},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3882037103176117},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.26186591386795044},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.13544857501983643}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8528544902801514},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8247874975204468},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6678853034973145},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.6499581933021545},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6276655197143555},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.6235239505767822},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6078684329986572},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5987356901168823},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.5672901272773743},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.48122477531433105},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.46816039085388184},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.44552505016326904},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.4363164007663727},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.43234843015670776},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.4316667914390564},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4223855137825012},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3882037103176117},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.26186591386795044},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.13544857501983643},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/msp.2017.2736018","is_oa":false,"landing_page_url":"https://doi.org/10.1109/msp.2017.2736018","pdf_url":null,"source":{"id":"https://openalex.org/S120977877","display_name":"IEEE Signal Processing Magazine","issn_l":"1053-5888","issn":["1053-5888","1558-0792"],"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 Signal Processing Magazine","raw_type":"journal-article"},{"id":"pmh:oai:ira.lib.polyu.edu.hk:10397/79834","is_oa":false,"landing_page_url":"http://hdl.handle.net/10397/79834","pdf_url":null,"source":{"id":"https://openalex.org/S4306400205","display_name":"PolyU Institutional Research Archive (Hong Kong Polytechnic University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I14243506","host_organization_name":"Hong Kong Polytechnic University","host_organization_lineage":["https://openalex.org/I14243506"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Journal/Magazine Article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1493093959","https://openalex.org/W1974013408","https://openalex.org/W1981572319","https://openalex.org/W1982471090","https://openalex.org/W1987489060","https://openalex.org/W1991329314","https://openalex.org/W2007795666","https://openalex.org/W2046119925","https://openalex.org/W2048042940","https://openalex.org/W2051596736","https://openalex.org/W2063855213","https://openalex.org/W2102166818","https://openalex.org/W2108598243","https://openalex.org/W2133257461","https://openalex.org/W2133665775","https://openalex.org/W2141983208","https://openalex.org/W2148848374","https://openalex.org/W2161907179","https://openalex.org/W2163922914","https://openalex.org/W2170319235","https://openalex.org/W2170947705","https://openalex.org/W2171349048","https://openalex.org/W2194775991","https://openalex.org/W2368744241","https://openalex.org/W2509123681","https://openalex.org/W2518824170","https://openalex.org/W2546855109","https://openalex.org/W2566149141","https://openalex.org/W2586275201","https://openalex.org/W2593290446","https://openalex.org/W2618530766","https://openalex.org/W2807793257","https://openalex.org/W2963918210","https://openalex.org/W3100404621","https://openalex.org/W6647225686","https://openalex.org/W6676297131","https://openalex.org/W6679718588","https://openalex.org/W6727127535"],"related_works":["https://openalex.org/W4312417841","https://openalex.org/W4321369474","https://openalex.org/W2731899572","https://openalex.org/W3133861977","https://openalex.org/W4200173597","https://openalex.org/W3116150086","https://openalex.org/W2999805992","https://openalex.org/W4380075502","https://openalex.org/W4291897433","https://openalex.org/W4223943233"],"abstract_inverted_index":{"Convolutional":[0],"neural":[1],"networks":[2],"(CNNs)":[3],"have":[4],"been":[5,28],"shown":[6],"to":[7,33,57,71,91],"deliver":[8,106],"standout":[9],"performance":[10],"on":[11,88,99],"a":[12,45,110],"wide":[13],"variety":[14],"of":[15,36,41,47,62,95],"visual":[16],"information":[17],"processing":[18],"applications.":[19],"However,":[20],"this":[21,81],"rapidly":[22,82],"developing":[23],"technology":[24],"has":[25,55],"only":[26],"recently":[27],"applied":[29],"with":[30,59],"systematic":[31],"energy":[32],"the":[34,60],"problem":[35],"picture-quality":[37,74,102,113],"prediction,":[38],"primarily":[39],"because":[40],"limitations":[42],"imposed":[43],"by":[44],"lack":[46],"adequate":[48],"ground-truth":[49,96],"human":[50],"subjective":[51],"data.":[52],"This":[53],"situation":[54],"begun":[56],"change":[58],"development":[61],"promising":[63],"data-gathering":[64],"methods":[65],"that":[66,105],"are":[67],"driving":[68],"new":[69,89],"approaches":[70],"deep-learning-based":[72],"perceptual":[73],"prediction.":[75],"Here,":[76],"we":[77],"assay":[78],"progress":[79],"in":[80,86,109],"evolving":[83],"field,":[84],"focusing,":[85],"particular,":[87],"ways":[90],"collect":[92],"large":[93],"quantities":[94],"data":[97],"and":[98],"recent":[100],"CNN-based":[101],"prediction":[103],"models":[104],"excellent":[107],"results":[108],"large,":[111],"real-world,":[112],"database.":[114]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":23},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":36},{"year":2022,"cited_by_count":34},{"year":2021,"cited_by_count":47},{"year":2020,"cited_by_count":49},{"year":2019,"cited_by_count":46},{"year":2018,"cited_by_count":34},{"year":2017,"cited_by_count":4}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
