{"id":"https://openalex.org/W2800765012","doi":"https://doi.org/10.1109/icassp.2018.8462369","title":"Deep Blind Image Quality Assessment by Learning Sensitivity Map","display_name":"Deep Blind Image Quality Assessment by Learning Sensitivity Map","publication_year":2018,"publication_date":"2018-04-01","ids":{"openalex":"https://openalex.org/W2800765012","doi":"https://doi.org/10.1109/icassp.2018.8462369","mag":"2800765012"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2018.8462369","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2018.8462369","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-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":["Yonsei University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yonsei University","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101619405","display_name":"Woojae Kim","orcid":"https://orcid.org/0000-0002-8312-9736"},"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":"Woojae Kim","raw_affiliation_strings":["Yonsei University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yonsei University","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"last","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":["Yonsei University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yonsei University","institution_ids":["https://openalex.org/I193775966"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.212,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.54011944,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"9394","issue":null,"first_page":"6727","last_page":"6731"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":0.9994999766349792,"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":0.9994999766349792,"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":0.9897000193595886,"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"}},{"id":"https://openalex.org/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9731000065803528,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/overfitting","display_name":"Overfitting","score":0.7962672710418701},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7619789838790894},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7617161273956299},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7020441293716431},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5541693568229675},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5423307418823242},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.5332901477813721},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.53106689453125},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4790176749229431},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.46277034282684326},{"id":"https://openalex.org/keywords/sensitivity","display_name":"Sensitivity (control systems)","score":0.46270042657852173},{"id":"https://openalex.org/keywords/quality-assessment","display_name":"Quality assessment","score":0.4514809548854828},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4382728338241577},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4124146103858948},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3910602331161499},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.17110693454742432}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.7962672710418701},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7619789838790894},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7617161273956299},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7020441293716431},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5541693568229675},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5423307418823242},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.5332901477813721},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.53106689453125},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4790176749229431},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.46277034282684326},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.46270042657852173},{"id":"https://openalex.org/C3020001037","wikidata":"https://www.wikidata.org/wiki/Q836575","display_name":"Quality assessment","level":3,"score":0.4514809548854828},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4382728338241577},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4124146103858948},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3910602331161499},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.17110693454742432},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"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/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2018.8462369","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2018.8462369","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.6600000262260437}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1974013408","https://openalex.org/W1977246677","https://openalex.org/W1977725648","https://openalex.org/W1981572319","https://openalex.org/W1982471090","https://openalex.org/W1987489060","https://openalex.org/W1991329314","https://openalex.org/W1999475542","https://openalex.org/W2051596736","https://openalex.org/W2108598243","https://openalex.org/W2133665775","https://openalex.org/W2141983208","https://openalex.org/W2161907179","https://openalex.org/W2162692770","https://openalex.org/W2170947705","https://openalex.org/W2171349048","https://openalex.org/W2566149141","https://openalex.org/W2737134362","https://openalex.org/W2767836774","https://openalex.org/W4239072543","https://openalex.org/W6631190155","https://openalex.org/W6649979526","https://openalex.org/W6663470086","https://openalex.org/W6741493709"],"related_works":["https://openalex.org/W1574414179","https://openalex.org/W4362597605","https://openalex.org/W2466958844","https://openalex.org/W2804751933","https://openalex.org/W2245293081","https://openalex.org/W1973829424","https://openalex.org/W3209787365","https://openalex.org/W4311304958","https://openalex.org/W1963681152","https://openalex.org/W4287019296"],"abstract_inverted_index":{"Applying":[0],"a":[1,14,22,30,61,71,86,115,123],"deep":[2],"convolutional":[3],"neural":[4],"network":[5],"CNN":[6],"to":[7,18,54],"no-reference":[8],"image":[9,45],"quality":[10],"assessment":[11],"(NR-IQA)":[12],"is":[13,66,82],"challenging":[15],"task":[16],"due":[17],"the":[19,58,77,94,101,105,109],"lack":[20],"of":[21,104],"training":[23,52,73],"database.":[24],"In":[25,57],"this":[26,38],"paper,":[27],"we":[28,112],"propose":[29],"CNN-based":[31],"NR-IQA":[32],"framework":[33],"that":[34,120],"can":[35],"effectively":[36],"solve":[37],"problem.":[39],"The":[40],"proposed":[41],"method-the":[42],"Deep":[43],"Blind":[44],"Quality":[46],"Assessment":[47],"predictor":[48],"(DeepBQA)-adopts":[49],"two":[50],"step":[51],"stages":[53],"avoid":[55],"overfitting.":[56],"first":[59],"stage,":[60,79],"ground-truth":[62],"objective":[63,96,106],"error":[64,97,107],"map":[65],"generated":[67],"and":[68],"used":[69],"as":[70],"proxy":[72],"target.":[74],"Then,":[75],"in":[76,93],"second":[78],"subjective":[80],"score":[81],"predicted":[83,95],"by":[84],"learning":[85],"sensitivity":[87],"map,":[88],"which":[89],"weights":[90],"each":[91],"pixel":[92],"map.":[98,117],"To":[99],"compensate":[100],"inaccurate":[102],"prediction":[103],"on":[108],"homogeneous":[110],"regions,":[111],"additionally":[113],"suggest":[114],"reliability":[116],"Experiments":[118],"showed":[119],"DeepBQA":[121],"yields":[122],"state-of-the-art":[124],"correlation":[125],"with":[126],"human":[127],"opinions.":[128]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}