{"id":"https://openalex.org/W2980441700","doi":"https://doi.org/10.1145/3347448.3357162","title":"A New Large-scale Food Image Segmentation Dataset and Its Application to Food Calorie Estimation Based on Grains of Rice","display_name":"A New Large-scale Food Image Segmentation Dataset and Its Application to Food Calorie Estimation Based on Grains of Rice","publication_year":2019,"publication_date":"2019-10-15","ids":{"openalex":"https://openalex.org/W2980441700","doi":"https://doi.org/10.1145/3347448.3357162","mag":"2980441700"},"language":"en","primary_location":{"id":"doi:10.1145/3347448.3357162","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3347448.3357162","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 5th International Workshop on Multimedia Assisted Dietary Management","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/A5061243963","display_name":"Takumi Ege","orcid":null},"institutions":[{"id":"https://openalex.org/I20529979","display_name":"University of Electro-Communications","ror":"https://ror.org/02x73b849","country_code":"JP","type":"education","lineage":["https://openalex.org/I20529979"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Takumi Ege","raw_affiliation_strings":["The University of Electro-Communications, Chofu, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"The University of Electro-Communications, Chofu, Tokyo, Japan","institution_ids":["https://openalex.org/I20529979"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051127663","display_name":"Wataru Shimoda","orcid":"https://orcid.org/0000-0001-6238-9697"},"institutions":[{"id":"https://openalex.org/I20529979","display_name":"University of Electro-Communications","ror":"https://ror.org/02x73b849","country_code":"JP","type":"education","lineage":["https://openalex.org/I20529979"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Wataru Shimoda","raw_affiliation_strings":["The University of Electro-Communications, Chofu, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"The University of Electro-Communications, Chofu, Tokyo, Japan","institution_ids":["https://openalex.org/I20529979"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054600485","display_name":"\u202aKeiji Yanai\u202c","orcid":"https://orcid.org/0000-0002-0431-183X"},"institutions":[{"id":"https://openalex.org/I20529979","display_name":"University of Electro-Communications","ror":"https://ror.org/02x73b849","country_code":"JP","type":"education","lineage":["https://openalex.org/I20529979"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Keiji Yanai","raw_affiliation_strings":["The University of Electro-Communications, Chofu, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"The University of Electro-Communications, Chofu, Tokyo, Japan","institution_ids":["https://openalex.org/I20529979"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5061243963"],"corresponding_institution_ids":["https://openalex.org/I20529979"],"apc_list":null,"apc_paid":null,"fwci":4.3924,"has_fulltext":false,"cited_by_count":53,"citation_normalized_percentile":{"value":0.94435877,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"82","last_page":"87"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10866","display_name":"Nutritional Studies and Diet","score":0.9897000193595886,"subfield":{"id":"https://openalex.org/subfields/2739","display_name":"Public Health, Environmental and Occupational Health"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10866","display_name":"Nutritional Studies and Diet","score":0.9897000193595886,"subfield":{"id":"https://openalex.org/subfields/2739","display_name":"Public Health, Environmental and Occupational Health"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9855999946594238,"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/T12388","display_name":"Identification and Quantification in Food","score":0.9761000275611877,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7356655597686768},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7010605335235596},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6424940228462219},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.6191227436065674},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.5612425208091736},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.505394458770752},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4985928535461426},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.49561750888824463},{"id":"https://openalex.org/keywords/minimum-bounding-box","display_name":"Minimum bounding box","score":0.4604196846485138},{"id":"https://openalex.org/keywords/food-energy","display_name":"Food energy","score":0.4584173560142517},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45645686984062195},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.42911675572395325},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.34400105476379395},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.13218283653259277},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.08054101467132568}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7356655597686768},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7010605335235596},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6424940228462219},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6191227436065674},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.5612425208091736},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.505394458770752},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4985928535461426},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.49561750888824463},{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.4604196846485138},{"id":"https://openalex.org/C116019233","wikidata":"https://www.wikidata.org/wiki/Q186205","display_name":"Food energy","level":2,"score":0.4584173560142517},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45645686984062195},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.42911675572395325},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.34400105476379395},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.13218283653259277},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.08054101467132568},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3347448.3357162","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3347448.3357162","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 5th International Workshop on Multimedia Assisted Dietary Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger","score":0.46000000834465027}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W12634471","https://openalex.org/W1030521295","https://openalex.org/W1686810756","https://openalex.org/W1901129140","https://openalex.org/W1964856489","https://openalex.org/W2057352599","https://openalex.org/W2087082746","https://openalex.org/W2091013587","https://openalex.org/W2124351162","https://openalex.org/W2206370378","https://openalex.org/W2256138263","https://openalex.org/W2530969395","https://openalex.org/W2531177272","https://openalex.org/W2560804113","https://openalex.org/W2570343428","https://openalex.org/W2963037989","https://openalex.org/W2964309882"],"related_works":["https://openalex.org/W1669643531","https://openalex.org/W2005437358","https://openalex.org/W2517104666","https://openalex.org/W1967061043","https://openalex.org/W2549936415","https://openalex.org/W4313854567","https://openalex.org/W2127194945","https://openalex.org/W1986943276","https://openalex.org/W2075289353","https://openalex.org/W4385421593"],"abstract_inverted_index":{"To":[0,44],"estimate":[1,45],"food":[2,6,9,18,36,67,103,120,131,157,168],"calorie":[3,121,132,169],"accurately":[4],"from":[5,162],"images,":[7,164],"accurate":[8,119,167],"image":[10,19,104],"segmentation":[11,20,32,46,77,98,108],"is":[12,114],"needed.":[13],"So":[14],"far":[15],"no":[16],"large-scale":[17],"datasets":[21],"which":[22,113,139,165],"have":[23],"pixel-wise":[24],"labels":[25],"exists.":[26],"In":[27,123],"this":[28],"paper,":[29],"we":[30,48,74,80,125,154],"added":[31],"masks":[33],"to":[34,116],"the":[35,39,54,93,101,152],"images":[37,85],"in":[38,53,143],"existing":[40],"dataset,":[41],"UEC-Food100,":[42],"semi-automatically.":[43],"masks,":[47,78],"revised":[49],"bounding":[50,59],"boxes":[51,60],"included":[52],"UEC-Food100":[55],"dataset":[56],"so":[57],"that":[58],"bounds":[61],"not":[62],"dish":[63],"regions":[64],"but":[65],"only":[66],"regions.":[68],"As":[69,106],"results,":[70,107],"by":[71,90],"applying":[72],"GrubCut,":[73],"obtained":[75],"good":[76],"and":[79,82],"checked":[81],"corrected":[83],"1000":[84],"of":[86,136,147],"them":[87],"if":[88],"needed":[89],"hand":[91],"for":[92],"testing":[94],"masks.":[95,105],"We":[96],"trained":[97],"networks":[99],"with":[100],"newly-created":[102],"accuracy":[109],"was":[110],"much":[111],"improved,":[112],"expected":[115],"bring":[117],"more":[118],"estimation.":[122,170],"addition,":[124],"propose":[126],"a":[127,148],"new":[128],"method":[129],"on":[130],"estimation":[133],"using":[134],"grains":[135],"steamed":[137],"rice":[138,163],"are":[140],"typically":[141],"contained":[142],"Japanese":[144],"foods":[145],"instead":[146],"reference":[149],"card.":[150],"By":[151],"experiments,":[153],"show":[155],"real":[156],"size":[158],"can":[159],"be":[160],"estimated":[161],"helps":[166]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":15},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}