{"id":"https://openalex.org/W2780534582","doi":"https://doi.org/10.1109/iccv.2017.613","title":"Deep Scene Image Classification with the MFAFVNet","display_name":"Deep Scene Image Classification with the MFAFVNet","publication_year":2017,"publication_date":"2017-10-01","ids":{"openalex":"https://openalex.org/W2780534582","doi":"https://doi.org/10.1109/iccv.2017.613","mag":"2780534582"},"language":"en","primary_location":{"id":"doi:10.1109/iccv.2017.613","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2017.613","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Computer Vision (ICCV)","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/A5101455771","display_name":"Yunsheng Li","orcid":"https://orcid.org/0000-0002-3868-7472"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California, San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yunsheng Li","raw_affiliation_strings":["University of California, San Diego, CA"],"affiliations":[{"raw_affiliation_string":"University of California, San Diego, CA","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078603640","display_name":"Mandar Dixit","orcid":null},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California, San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mandar Dixit","raw_affiliation_strings":["University of California, San Diego, CA"],"affiliations":[{"raw_affiliation_string":"University of California, San Diego, CA","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043325212","display_name":"Nuno Vasconcelos","orcid":"https://orcid.org/0000-0002-9024-4302"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California, San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nuno Vasconcelos","raw_affiliation_strings":["University of California, San Diego, CA"],"affiliations":[{"raw_affiliation_string":"University of California, San Diego, CA","institution_ids":["https://openalex.org/I36258959"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101455771"],"corresponding_institution_ids":["https://openalex.org/I36258959"],"apc_list":null,"apc_paid":null,"fwci":1.8204,"has_fulltext":false,"cited_by_count":67,"citation_normalized_percentile":{"value":0.91721495,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9997000098228455,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9997000098228455,"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9977999925613403,"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"}},{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9976999759674072,"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":0.8211405277252197},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6520064473152161},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.6093252897262573},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.6078884601593018},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5985129475593567},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5687299966812134},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.5235611796379089},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4978506565093994},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.49622517824172974},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.4621278941631317},{"id":"https://openalex.org/keywords/network-architecture","display_name":"Network architecture","score":0.459696888923645},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4490549862384796},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.446450412273407},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.44389069080352783},{"id":"https://openalex.org/keywords/implementation","display_name":"Implementation","score":0.4247854948043823},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4228721261024475},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.35803472995758057},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1809774935245514}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8211405277252197},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6520064473152161},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.6093252897262573},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.6078884601593018},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5985129475593567},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5687299966812134},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.5235611796379089},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4978506565093994},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.49622517824172974},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.4621278941631317},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.459696888923645},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4490549862384796},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.446450412273407},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.44389069080352783},{"id":"https://openalex.org/C26713055","wikidata":"https://www.wikidata.org/wiki/Q245962","display_name":"Implementation","level":2,"score":0.4247854948043823},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4228721261024475},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.35803472995758057},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1809774935245514},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"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/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccv.2017.613","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2017.613","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.5,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W99353449","https://openalex.org/W1524680991","https://openalex.org/W1536680647","https://openalex.org/W1566135517","https://openalex.org/W1606858007","https://openalex.org/W1662191912","https://openalex.org/W1686810756","https://openalex.org/W1909952827","https://openalex.org/W1924160326","https://openalex.org/W1966385142","https://openalex.org/W2012592962","https://openalex.org/W2017814585","https://openalex.org/W2024197741","https://openalex.org/W2102605133","https://openalex.org/W2104657103","https://openalex.org/W2108598243","https://openalex.org/W2129326773","https://openalex.org/W2134670479","https://openalex.org/W2151103935","https://openalex.org/W2152161678","https://openalex.org/W2161969291","https://openalex.org/W2163605009","https://openalex.org/W2169177311","https://openalex.org/W2191616647","https://openalex.org/W2395325225","https://openalex.org/W2500786414","https://openalex.org/W2556382245","https://openalex.org/W2620629206","https://openalex.org/W2951019013","https://openalex.org/W2963066927","https://openalex.org/W6636412649","https://openalex.org/W6640081599","https://openalex.org/W6676297131","https://openalex.org/W6679431263","https://openalex.org/W6679792166","https://openalex.org/W6684191040","https://openalex.org/W6684872329","https://openalex.org/W6730368104"],"related_works":["https://openalex.org/W4254199101","https://openalex.org/W1670153145","https://openalex.org/W4236907339","https://openalex.org/W4300427796","https://openalex.org/W4287196534","https://openalex.org/W2051864124","https://openalex.org/W2155006800","https://openalex.org/W4299904075","https://openalex.org/W4387272257","https://openalex.org/W4200301313"],"abstract_inverted_index":{"The":[0,57],"problem":[1],"of":[2,15,24,29,41,63,73,79,90,119,143],"transferring":[3],"a":[4,42,64,69,77,97,103,117,128],"deep":[5],"convolutional":[6],"network":[7,43,80],"trained":[8,50],"for":[9],"object":[10],"recognition":[11],"to":[12,54,86,109,133],"the":[13,25,39,45,61,74,93,113,120,139,144],"task":[14],"scene":[16,148],"image":[17],"classification":[18],"is":[19,35,124],"considered.":[20],"An":[21],"embedded":[22,126],"implementation":[23],"recently":[26],"proposed":[27],"mixture":[28],"factor":[30],"analyzers":[31],"Fisher":[32,91],"vector":[33],"(MFA-FV)":[34],"proposed.":[36],"This":[37,130],"enables":[38,131],"design":[40,62],"architecture,":[44],"MFAFVNet,":[46],"that":[47,67,138],"can":[48],"be":[49],"in":[51],"an":[52],"end":[53,55,132,134],"manner.":[56],"new":[58],"architecture":[59],"involves":[60],"MFA-FV":[65],"layer":[66],"implements":[68],"statistically":[70],"correct":[71],"version":[72],"MFA-FV,":[75],"through":[76],"combination":[78],"computations":[81],"and":[82,102],"regularization.":[83],"When":[84,107],"compared":[85,108],"previous":[87,110],"neural":[88],"implementations":[89],"vectors,":[92],"MFAFVNet":[94,114,140],"relies":[95,115],"on":[96,116,147],"more":[98,104],"powerful":[99],"statistical":[100],"model":[101],"accurate":[105],"implementation.":[106],"non-embedded":[111],"models,":[112],"state":[118,142],"art":[121,145],"model,":[122],"which":[123],"now":[125],"into":[127],"CNN.":[129],"training.":[135],"Experiments":[136],"show":[137],"has":[141],"performance":[146],"classification.":[149]},"counts_by_year":[{"year":2025,"cited_by_count":14},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":10},{"year":2018,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}