{"id":"https://openalex.org/W2754213847","doi":"https://doi.org/10.1109/tip.2018.2831899","title":"NIMA: Neural Image Assessment","display_name":"NIMA: Neural Image Assessment","publication_year":2018,"publication_date":"2018-04-30","ids":{"openalex":"https://openalex.org/W2754213847","doi":"https://doi.org/10.1109/tip.2018.2831899","mag":"2754213847","pmid":"https://pubmed.ncbi.nlm.nih.gov/29994025"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2018.2831899","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tip.2018.2831899","pdf_url":"https://ieeexplore.ieee.org/ielx7/83/8347140/08352823.pdf","source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://ieeexplore.ieee.org/ielx7/83/8347140/08352823.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Hossein Talebi","orcid":"https://orcid.org/0000-0002-5962-2563"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Hossein Talebi","raw_affiliation_strings":["Google Inc, Mountain View, CA, US"],"affiliations":[{"raw_affiliation_string":"Google Inc, Mountain View, CA, US","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"last","author":{"id":null,"display_name":"Peyman Milanfar","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Peyman Milanfar","raw_affiliation_strings":["Google Inc, Mountain View, CA, US"],"affiliations":[{"raw_affiliation_string":"Google Inc, Mountain View, CA, US","institution_ids":["https://openalex.org/I1291425158"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I1291425158"],"apc_list":null,"apc_paid":null,"fwci":25.9241,"has_fulltext":true,"cited_by_count":899,"citation_normalized_percentile":{"value":0.99616161,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"27","issue":"8","first_page":"3998","last_page":"4011"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":0.7551000118255615,"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":0.7551000118255615,"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":0.1678999960422516,"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/T11019","display_name":"Image Enhancement Techniques","score":0.015200000256299973,"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/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6820999979972839},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.527899980545044},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5078999996185303},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.47589999437332153},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.43950000405311584},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4390000104904175},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.41100001335144043},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4099000096321106},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.4097999930381775}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7907999753952026},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7828999757766724},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6820999979972839},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.527899980545044},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5078999996185303},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.47589999437332153},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.43950000405311584},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4390000104904175},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.414000004529953},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.41100001335144043},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4099000096321106},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.4097999930381775},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.39070001244544983},{"id":"https://openalex.org/C3020001037","wikidata":"https://www.wikidata.org/wiki/Q836575","display_name":"Quality assessment","level":3,"score":0.38940000534057617},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.38920000195503235},{"id":"https://openalex.org/C62897895","wikidata":"https://www.wikidata.org/wiki/Q1915482","display_name":"Mean opinion score","level":3,"score":0.38019999861717224},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.375},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3716000020503998},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.3628999888896942},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3598000109195709},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.3571000099182129},{"id":"https://openalex.org/C2779346075","wikidata":"https://www.wikidata.org/wiki/Q7268763","display_name":"Quality Score","level":3,"score":0.33390000462532043},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.30979999899864197},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.3061999976634979},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.3034999966621399},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.27639999985694885},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.2603999972343445}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tip.2018.2831899","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tip.2018.2831899","pdf_url":"https://ieeexplore.ieee.org/ielx7/83/8347140/08352823.pdf","source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},{"id":"pmid:29994025","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/29994025","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on image processing : a publication of the IEEE Signal Processing Society","raw_type":null},{"id":"pmh:oai:arXiv.org:1709.05424","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1709.05424","pdf_url":"https://arxiv.org/pdf/1709.05424","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.1109/tip.2018.2831899","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tip.2018.2831899","pdf_url":"https://ieeexplore.ieee.org/ielx7/83/8347140/08352823.pdf","source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2754213847.pdf","grobid_xml":"https://content.openalex.org/works/W2754213847.grobid-xml"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W1896080482","https://openalex.org/W1971014006","https://openalex.org/W1982471090","https://openalex.org/W2009678853","https://openalex.org/W2051596736","https://openalex.org/W2078807908","https://openalex.org/W2129644086","https://openalex.org/W2133665775","https://openalex.org/W2148848374","https://openalex.org/W2162692770","https://openalex.org/W2162915697","https://openalex.org/W2163084851","https://openalex.org/W2171125155","https://openalex.org/W2171349048","https://openalex.org/W2183341477","https://openalex.org/W2217895792","https://openalex.org/W2293846591","https://openalex.org/W2295185217","https://openalex.org/W2406273144","https://openalex.org/W2467531333","https://openalex.org/W2473697052","https://openalex.org/W2509123681","https://openalex.org/W2514295308","https://openalex.org/W2515223471","https://openalex.org/W2604528050","https://openalex.org/W2767836774","https://openalex.org/W2963082084","https://openalex.org/W4247811648","https://openalex.org/W6638667902","https://openalex.org/W6684191040","https://openalex.org/W6684791271","https://openalex.org/W6713134421","https://openalex.org/W6717040974","https://openalex.org/W6745992419","https://openalex.org/W6748197083"],"related_works":[],"abstract_inverted_index":{"Automatically":[0],"learned":[1],"quality":[2,165],"assessment":[3],"for":[4,152,159],"images":[5,121],"has":[6,82],"recently":[7],"become":[8],"a":[9,17,75,143,153],"hot":[10],"topic":[11],"due":[12],"to":[13,117,127,132],"its":[14],"usefulness":[15],"in":[16,64,142],"wide":[18],"variety":[19],"of":[20,37,70,85,104,138],"applications":[21],"such":[22,52],"as":[23,53],"evaluating":[24],"image":[25],"capture":[26],"pipelines,":[27],"storage":[28],"techniques":[29],"and":[30,56,123,136,162],"sharing":[31],"media.":[32],"Despite":[33],"the":[34,45,68,83,100],"subjective":[35],"nature":[36],"this":[38,147],"problem,":[39],"most":[40],"existing":[41],"methods":[42,91],"only":[43,119],"predict":[44,67],"mean":[46],"opinion":[47,72],"score":[48,120],"provided":[49],"by":[50],"datasets":[51],"AVA":[54],"[1]":[55],"TID2013":[57],"[2].":[58],"Our":[59,79,95,111],"approach":[60,97],"differs":[61],"from":[62],"others":[63],"that":[65],"we":[66],"distribution":[69],"human":[71,128],"scores":[73],"using":[74],"convolutional":[76],"neural":[77],"network.":[78],"architecture":[80],"also":[81,131],"advantage":[84],"being":[86],"significantly":[87],"simpler":[88],"than":[89],"other":[90],"with":[92,124,134],"comparable":[93],"performance.":[94],"proposed":[96],"relies":[98],"on":[99],"success":[101],"(and":[102],"retraining)":[103],"proven,":[105],"state-of-the-art":[106],"deep":[107],"object":[108],"recognition":[109],"networks.":[110],"resulting":[112],"network":[113],"can":[114],"be":[115],"used":[116],"not":[118],"reliably":[122],"high":[125],"correlation":[126],"perception,":[129],"but":[130],"assist":[133],"adaptation":[135],"optimization":[137],"photo":[139],"editing/enhancement":[140],"algorithms":[141],"photographic":[144],"pipeline.":[145],"All":[146],"is":[148],"done":[149],"without":[150],"need":[151],"\"golden\"":[154],"reference":[155],"image,":[156],"consequently":[157],"allowing":[158],"single-image,":[160],"semantic-":[161],"perceptually-aware,":[163],"no-reference":[164],"assessment.":[166]},"counts_by_year":[{"year":2026,"cited_by_count":38},{"year":2025,"cited_by_count":160},{"year":2024,"cited_by_count":159},{"year":2023,"cited_by_count":159},{"year":2022,"cited_by_count":139},{"year":2021,"cited_by_count":99},{"year":2020,"cited_by_count":80},{"year":2019,"cited_by_count":58},{"year":2018,"cited_by_count":7}],"updated_date":"2026-04-12T07:58:50.170612","created_date":"2017-09-25T00:00:00"}
