{"id":"https://openalex.org/W2163969215","doi":"https://doi.org/10.1145/2647868.2654970","title":"Food Detection and Recognition Using Convolutional Neural Network","display_name":"Food Detection and Recognition Using Convolutional Neural Network","publication_year":2014,"publication_date":"2014-11-03","ids":{"openalex":"https://openalex.org/W2163969215","doi":"https://doi.org/10.1145/2647868.2654970","mag":"2163969215"},"language":"en","primary_location":{"id":"doi:10.1145/2647868.2654970","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2647868.2654970","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 22nd ACM international conference on Multimedia","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/A5037422132","display_name":"Hokuto Kagaya","orcid":null},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Hokuto Kagaya","raw_affiliation_strings":["The University of Tokyo, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"The University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069982192","display_name":"Kiyoharu Aizawa","orcid":"https://orcid.org/0000-0003-2146-6275"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kiyoharu Aizawa","raw_affiliation_strings":["The University of Tokyo, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"The University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061491407","display_name":"Makoto Ogawa","orcid":"https://orcid.org/0000-0002-3781-2016"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Makoto Ogawa","raw_affiliation_strings":["foo.log Inc., Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"foo.log Inc., Tokyo, Japan","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5037422132"],"corresponding_institution_ids":["https://openalex.org/I74801974"],"apc_list":null,"apc_paid":null,"fwci":8.6573,"has_fulltext":false,"cited_by_count":305,"citation_normalized_percentile":{"value":0.98297216,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1085","last_page":"1088"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9919999837875366,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9919999837875366,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T10616","display_name":"Smart Agriculture and AI","score":0.9847999811172485,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T14319","display_name":"Currency Recognition and Detection","score":0.968999981880188,"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":0.8751396536827087},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8120386004447937},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7821934223175049},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6905574202537537},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6398070454597473},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5508263111114502},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5297081470489502},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5048969388008118},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.43668538331985474},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4283289313316345},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4202845096588135},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3713786005973816},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3637387156486511}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8751396536827087},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8120386004447937},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7821934223175049},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6905574202537537},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6398070454597473},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5508263111114502},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5297081470489502},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5048969388008118},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.43668538331985474},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4283289313316345},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4202845096588135},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3713786005973816},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3637387156486511},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2647868.2654970","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2647868.2654970","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 22nd ACM international conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5,"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"},{"id":"https://openalex.org/F4320338075","display_name":"Core Research for Evolutional Science and Technology","ror":"https://ror.org/00097mb19"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1978132383","https://openalex.org/W2026845913","https://openalex.org/W2055527244","https://openalex.org/W2096761622","https://openalex.org/W2097018403","https://openalex.org/W2105997696","https://openalex.org/W2109257383","https://openalex.org/W2112796928","https://openalex.org/W2120480077","https://openalex.org/W2130448385","https://openalex.org/W2155091972","https://openalex.org/W2163605009","https://openalex.org/W2253807446"],"related_works":["https://openalex.org/W2964954556","https://openalex.org/W2911497689","https://openalex.org/W2952813363","https://openalex.org/W2963346891","https://openalex.org/W4360783045","https://openalex.org/W2770149305","https://openalex.org/W3167930666","https://openalex.org/W3014952856","https://openalex.org/W3010730661","https://openalex.org/W2565656575"],"abstract_inverted_index":{"In":[0,111],"this":[1],"paper,":[2],"we":[3,113],"apply":[4],"a":[5,46,55,77,86,138],"convolutional":[6],"neural":[7],"network":[8],"(CNN)":[9],"to":[10,44,58,64,94],"the":[11,21,65,80,116,123],"tasks":[12,66],"of":[13,20,24,26,30,67,79],"detecting":[14],"and":[15,52,70,91],"recognizing":[16],"food":[17,31,68,83,128],"images.":[18],"Because":[19],"wide":[22],"diversity":[23],"types":[25],"food,":[27],"image":[28,49,129],"recognition":[29,50,71,96],"items":[32,84],"is":[33,54],"generally":[34],"very":[35,47],"difficult.":[36],"However,":[37],"deep":[38,59],"learning":[39],"has":[40],"been":[41],"shown":[42],"recently":[43],"be":[45],"powerful":[48],"technique,":[51],"CNN":[53,63,98,131],"state-of-the-art":[56],"approach":[57],"learning.":[60],"We":[61,75],"applied":[62],"detection":[69],"through":[72],"parameter":[73],"optimization.":[74],"constructed":[76],"dataset":[78],"most":[81],"frequent":[82],"in":[85],"publicly":[87],"available":[88],"food-logging":[89],"system,":[90],"used":[92],"it":[93],"evaluate":[95],"performance.":[97],"showed":[99,133],"significantly":[100,134],"higher":[101,135],"accuracy":[102,136],"than":[103,137],"did":[104],"traditional":[105],"support-vector-machine-based":[106],"methods":[107],"with":[108],"handcrafted":[109],"features.":[110],"addition,":[112],"found":[114],"that":[115,120],"convolution":[117],"kernels":[118],"show":[119],"color":[121],"dominates":[122],"feature":[124],"extraction":[125],"process.":[126],"For":[127],"detection,":[130],"also":[132],"conventional":[139],"method":[140],"did.":[141]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":22},{"year":2024,"cited_by_count":29},{"year":2023,"cited_by_count":34},{"year":2022,"cited_by_count":33},{"year":2021,"cited_by_count":30},{"year":2020,"cited_by_count":41},{"year":2019,"cited_by_count":41},{"year":2018,"cited_by_count":28},{"year":2017,"cited_by_count":20},{"year":2016,"cited_by_count":17},{"year":2015,"cited_by_count":8}],"updated_date":"2026-04-12T07:58:50.170612","created_date":"2025-10-10T00:00:00"}
