{"id":"https://openalex.org/W4379653395","doi":"https://doi.org/10.1117/12.2679721","title":"Semantic food segmentation for health monitoring","display_name":"Semantic food segmentation for health monitoring","publication_year":2023,"publication_date":"2023-06-07","ids":{"openalex":"https://openalex.org/W4379653395","doi":"https://doi.org/10.1117/12.2679721"},"language":"en","primary_location":{"id":"doi:10.1117/12.2679721","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1117/12.2679721","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Fifteenth International Conference on Machine Vision (ICMV 2022)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5075319234","display_name":"Mazhar Hussain","orcid":"https://orcid.org/0000-0001-5054-6317"},"institutions":[{"id":"https://openalex.org/I39063666","display_name":"University of Catania","ror":"https://ror.org/03a64bh57","country_code":"IT","type":"education","lineage":["https://openalex.org/I39063666"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Mazhar Hussain","raw_affiliation_strings":["Univ. of Catania (Italy)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ. of Catania (Italy)","institution_ids":["https://openalex.org/I39063666"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076307306","display_name":"Alessandro Ortis","orcid":"https://orcid.org/0000-0003-3461-4679"},"institutions":[{"id":"https://openalex.org/I39063666","display_name":"University of Catania","ror":"https://ror.org/03a64bh57","country_code":"IT","type":"education","lineage":["https://openalex.org/I39063666"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Alessandro Ortis","raw_affiliation_strings":["Univ. of Catania (Italy)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ. of Catania (Italy)","institution_ids":["https://openalex.org/I39063666"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055766018","display_name":"Riccardo Polosa","orcid":"https://orcid.org/0000-0002-8450-5721"},"institutions":[{"id":"https://openalex.org/I39063666","display_name":"University of Catania","ror":"https://ror.org/03a64bh57","country_code":"IT","type":"education","lineage":["https://openalex.org/I39063666"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Riccardo Polosa","raw_affiliation_strings":["ECLAT S.r.L. (Italy)","Univ. of Catania (Italy)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ECLAT S.r.L. (Italy)","institution_ids":[]},{"raw_affiliation_string":"Univ. of Catania (Italy)","institution_ids":["https://openalex.org/I39063666"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042746008","display_name":"Sebastiano Battiato","orcid":"https://orcid.org/0000-0001-6127-2470"},"institutions":[{"id":"https://openalex.org/I39063666","display_name":"University of Catania","ror":"https://ror.org/03a64bh57","country_code":"IT","type":"education","lineage":["https://openalex.org/I39063666"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Sebastiano Battiato","raw_affiliation_strings":["Univ. of Catania (Italy)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ. of Catania (Italy)","institution_ids":["https://openalex.org/I39063666"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I39063666"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.09297164,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"34","last_page":"34"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9943000078201294,"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":0.9943000078201294,"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/T10866","display_name":"Nutritional Studies and Diet","score":0.9487000107765198,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7842692136764526},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.6893752217292786},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6787664890289307},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6105403304100037},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5878890156745911},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5422594547271729},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.526984691619873},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4640592336654663},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.46060898900032043},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4321654438972473},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.42057496309280396},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.09130948781967163},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.07230335474014282},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.06432411074638367}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7842692136764526},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.6893752217292786},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6787664890289307},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6105403304100037},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5878890156745911},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5422594547271729},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.526984691619873},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4640592336654663},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.46060898900032043},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4321654438972473},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.42057496309280396},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.09130948781967163},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.07230335474014282},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.06432411074638367},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"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:10.1117/12.2679721","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1117/12.2679721","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Fifteenth International Conference on Machine Vision (ICMV 2022)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Zero hunger","score":0.6100000143051147,"id":"https://metadata.un.org/sdg/2"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2517104666","https://openalex.org/W2005437358","https://openalex.org/W1669643531","https://openalex.org/W2039154422","https://openalex.org/W2008656436","https://openalex.org/W2134924024","https://openalex.org/W2023558673","https://openalex.org/W2110230079","https://openalex.org/W1982826852","https://openalex.org/W2613186388"],"abstract_inverted_index":{"This":[0,108],"paper":[1],"presents":[2],"semantic":[3,71,99,123,132],"food":[4,9,53,67,76,94,145],"segmentation":[5,54,95,133,140],"to":[6,29,36,56,73,96,115],"detect":[7],"individual":[8,75],"items":[10,68,77],"in":[11,20,79],"an":[12,33,80,102],"image.":[13,81,146],"The":[14,50],"presented":[15],"approach":[16],"has":[17],"been":[18],"developed":[19],"the":[21,24,40,64,98,130,143,148],"context":[22],"of":[23,43,52,66,101,142],"FoodRec":[25],"project,":[26],"which":[27],"aims":[28],"study":[30],"and":[31,38,69,112,120,138],"develop":[32],"automatic":[34],"framework":[35],"track":[37],"monitor":[39],"dietary":[41],"habits":[42],"people,":[44],"during":[45],"their":[46],"smoke":[47],"quitting":[48],"protocol.":[49],"goal":[51],"is":[55],"train":[57],"a":[58,87,105,117,128,136,155],"model":[59],"that":[60],"can":[61],"look":[62],"at":[63,104],"images":[65],"infer":[70],"information":[72,100],"recognize":[74],"present":[78],"In":[82],"this":[83],"contribution,":[84],"we":[85],"propose":[86],"novel":[88,131],"Convolutional":[89],"Deconvolutional":[90],"Pyramid":[91],"Network":[92],"for":[93],"understand":[97],"image":[103],"pixel":[106],"level.":[107],"network":[109,134],"employs":[110],"convolution":[111],"deconvolution":[113],"layers":[114],"build":[116],"feature":[118,124],"pyramid":[119],"achieves":[121],"high-level":[122],"map":[125,141],"representation.":[126],"As":[127],"consequence,":[129],"generates":[135],"dense":[137],"precise":[139],"input":[144],"Furthermore,":[147],"proposed":[149],"method":[150],"demonstrated":[151],"significant":[152],"improvements":[153],"on":[154],"well-known":[156],"public":[157],"benchmark":[158],"dataset.":[159]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
