{"id":"https://openalex.org/W3017284158","doi":"https://doi.org/10.1109/icaiic48513.2020.9065281","title":"Food Image Recognition Based on Densely Connected Convolutional Neural Networks","display_name":"Food Image Recognition Based on Densely Connected Convolutional Neural Networks","publication_year":2020,"publication_date":"2020-02-01","ids":{"openalex":"https://openalex.org/W3017284158","doi":"https://doi.org/10.1109/icaiic48513.2020.9065281","mag":"3017284158"},"language":"en","primary_location":{"id":"doi:10.1109/icaiic48513.2020.9065281","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icaiic48513.2020.9065281","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","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/A5039122452","display_name":"Al-Selwi Metwalli","orcid":null},"institutions":[{"id":"https://openalex.org/I1328775524","display_name":"Zhejiang Sci-Tech University","ror":"https://ror.org/03893we55","country_code":"CN","type":"education","lineage":["https://openalex.org/I1328775524"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Al-Selwi Metwalli","raw_affiliation_strings":["School of Informatics, Zhejiang Sci-Tech University, Hangzhou, Zhejiang, China"],"affiliations":[{"raw_affiliation_string":"School of Informatics, Zhejiang Sci-Tech University, Hangzhou, Zhejiang, China","institution_ids":["https://openalex.org/I1328775524"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048353325","display_name":"Wei Shen","orcid":"https://orcid.org/0000-0002-1235-598X"},"institutions":[{"id":"https://openalex.org/I1328775524","display_name":"Zhejiang Sci-Tech University","ror":"https://ror.org/03893we55","country_code":"CN","type":"education","lineage":["https://openalex.org/I1328775524"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Shen","raw_affiliation_strings":["School of Informatics, Zhejiang Sci-Tech University, Hangzhou, Zhejiang, China"],"affiliations":[{"raw_affiliation_string":"School of Informatics, Zhejiang Sci-Tech University, Hangzhou, Zhejiang, China","institution_ids":["https://openalex.org/I1328775524"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054307870","display_name":"Chase Q. Wu","orcid":"https://orcid.org/0000-0002-8218-1209"},"institutions":[{"id":"https://openalex.org/I118118575","display_name":"New Jersey Institute of Technology","ror":"https://ror.org/05e74xb87","country_code":"US","type":"education","lineage":["https://openalex.org/I118118575"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chase Q. Wu","raw_affiliation_strings":["Department of Computer Science, New Jersey Institute of Technology, Newark, NJ, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, New Jersey Institute of Technology, Newark, NJ, USA","institution_ids":["https://openalex.org/I118118575"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5039122452"],"corresponding_institution_ids":["https://openalex.org/I1328775524"],"apc_list":null,"apc_paid":null,"fwci":1.3678,"has_fulltext":false,"cited_by_count":29,"citation_normalized_percentile":{"value":0.83252672,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"027","last_page":"032"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.991599977016449,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.991599977016449,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9883000254631042,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9869999885559082,"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/softmax-function","display_name":"Softmax function","score":0.9201862812042236},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.8452240228652954},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8115171790122986},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6946373581886292},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6709896326065063},{"id":"https://openalex.org/keywords/variation","display_name":"Variation (astronomy)","score":0.5491495132446289},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4901929497718811},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4859848916530609},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4571336507797241},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.43927961587905884},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.43675389885902405}],"concepts":[{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.9201862812042236},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8452240228652954},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8115171790122986},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6946373581886292},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6709896326065063},{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.5491495132446289},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4901929497718811},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4859848916530609},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4571336507797241},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.43927961587905884},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.43675389885902405},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"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/C44870925","wikidata":"https://www.wikidata.org/wiki/Q37547","display_name":"Astrophysics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icaiic48513.2020.9065281","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icaiic48513.2020.9065281","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5099999904632568,"display_name":"Zero hunger","id":"https://metadata.un.org/sdg/2"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W12634471","https://openalex.org/W1030521295","https://openalex.org/W1982635469","https://openalex.org/W2097117768","https://openalex.org/W2163605009","https://openalex.org/W2293499654","https://openalex.org/W2353070889","https://openalex.org/W2518108298","https://openalex.org/W2530422462","https://openalex.org/W2531634031","https://openalex.org/W2547831726","https://openalex.org/W2560376762","https://openalex.org/W2570343428","https://openalex.org/W2583892095","https://openalex.org/W2609569447","https://openalex.org/W2643943583","https://openalex.org/W2756066007","https://openalex.org/W2756716612","https://openalex.org/W2781923075","https://openalex.org/W2897198377","https://openalex.org/W2902817448","https://openalex.org/W2906920259","https://openalex.org/W2962901913","https://openalex.org/W2963217233","https://openalex.org/W2963263347","https://openalex.org/W2963285578","https://openalex.org/W2963446712","https://openalex.org/W2964350391","https://openalex.org/W3099451302","https://openalex.org/W3101227480","https://openalex.org/W3105026157","https://openalex.org/W4300289909","https://openalex.org/W6684191040","https://openalex.org/W6685562342","https://openalex.org/W6694260854","https://openalex.org/W6726497184","https://openalex.org/W6730423007","https://openalex.org/W6732510234","https://openalex.org/W6745798339"],"related_works":["https://openalex.org/W2899027234","https://openalex.org/W2997424368","https://openalex.org/W2911497689","https://openalex.org/W4229443568","https://openalex.org/W2952813363","https://openalex.org/W4360783045","https://openalex.org/W2963346891","https://openalex.org/W2770149305","https://openalex.org/W3167930666","https://openalex.org/W3014952856"],"abstract_inverted_index":{"Convolutional":[0],"neural":[1,33],"networks":[2],"have":[3],"been":[4],"widely":[5],"used":[6,50],"for":[7],"image":[8],"recognition":[9],"as":[10],"they":[11],"are":[12,80],"capable":[13],"of":[14,38,43,112],"extracting":[15],"features":[16,97],"with":[17],"high":[18],"accuracy.":[19],"In":[20,85],"this":[21],"paper,":[22],"we":[23,87],"propose":[24],"a":[25],"DenseFood":[26,107],"model":[27,108],"based":[28],"on":[29],"densely":[30],"connected":[31],"convolutional":[32],"network":[34],"architecture,":[35],"which":[36],"consists":[37],"multiple":[39],"layers.":[40],"A":[41],"combination":[42],"softmax":[44],"loss":[45,48],"and":[46,63,78,92,114],"center":[47],"is":[49],"during":[51],"the":[52,57,60,65,99,105,116],"training":[53],"process":[54],"to":[55,95],"minimize":[56],"variation":[58,66],"within":[59],"same":[61],"category":[62],"maximize":[64],"across":[67],"different":[68],"ones.":[69],"For":[70],"performance":[71],"comparison,":[72],"three":[73],"models,":[74],"namely,":[75],"DenseFood,":[76],"DenseNet121,":[77],"ResNet50":[79,93],"trained":[81],"using":[82],"VIREO-172":[83],"dataset.":[84,100],"addition,":[86],"fine":[88],"tune":[89],"pre-trained":[90],"DenseNet121":[91],"models":[94,118],"extract":[96],"from":[98],"Experimental":[101],"results":[102],"show":[103],"that":[104],"proposed":[106],"achieves":[109],"an":[110],"accuracy":[111],"81.23%":[113],"outperforms":[115],"other":[117],"in":[119],"comparison.":[120]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}