{"id":"https://openalex.org/W3209749315","doi":"https://doi.org/10.1109/icccnt51525.2021.9580174","title":"Cosmetic Skin Type Classification Using CNN With Product Recommendation","display_name":"Cosmetic Skin Type Classification Using CNN With Product Recommendation","publication_year":2021,"publication_date":"2021-07-06","ids":{"openalex":"https://openalex.org/W3209749315","doi":"https://doi.org/10.1109/icccnt51525.2021.9580174","mag":"3209749315"},"language":"en","primary_location":{"id":"doi:10.1109/icccnt51525.2021.9580174","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icccnt51525.2021.9580174","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 12th International Conference on Computing Communication and Networking Technologies (ICCCNT)","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/A5070107185","display_name":"Arya Kothari","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Arya Kothari","raw_affiliation_strings":["Sardar Patel Institute of Technology, Mumbai, India"],"affiliations":[{"raw_affiliation_string":"Sardar Patel Institute of Technology, Mumbai, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040863732","display_name":"Dipam Shah","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dipam Shah","raw_affiliation_strings":["Sardar Patel Institute of Technology, Mumbai, India"],"affiliations":[{"raw_affiliation_string":"Sardar Patel Institute of Technology, Mumbai, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078685502","display_name":"Taksh Soni","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Taksh Soni","raw_affiliation_strings":["Sardar Patel Institute of Technology, Mumbai, India"],"affiliations":[{"raw_affiliation_string":"Sardar Patel Institute of Technology, Mumbai, India","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010992762","display_name":"Sudhir Dhage","orcid":"https://orcid.org/0000-0001-8100-8941"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sudhir Dhage","raw_affiliation_strings":["Sardar Patel Institute of Technology, Mumbai, India"],"affiliations":[{"raw_affiliation_string":"Sardar Patel Institute of Technology, Mumbai, India","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5070107185"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.0568,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.79408497,"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":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9763000011444092,"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/T11448","display_name":"Face recognition and analysis","score":0.9763000011444092,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9545999765396118,"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/T10392","display_name":"Cutaneous Melanoma Detection and Management","score":0.9377999901771545,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"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/convolutional-neural-network","display_name":"Convolutional neural network","score":0.739002525806427},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7354714870452881},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7308986186981201},{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.680626392364502},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5982058048248291},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5930560827255249},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4710680842399597},{"id":"https://openalex.org/keywords/dry-skin","display_name":"Dry skin","score":0.464669793844223},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.4605836272239685},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.44349780678749084},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.32723480463027954},{"id":"https://openalex.org/keywords/dermatology","display_name":"Dermatology","score":0.22436103224754333},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14046090841293335},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.07185319066047668}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.739002525806427},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7354714870452881},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7308986186981201},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.680626392364502},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5982058048248291},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5930560827255249},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4710680842399597},{"id":"https://openalex.org/C2777035695","wikidata":"https://www.wikidata.org/wiki/Q1929023","display_name":"Dry skin","level":2,"score":0.464669793844223},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.4605836272239685},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.44349780678749084},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.32723480463027954},{"id":"https://openalex.org/C16005928","wikidata":"https://www.wikidata.org/wiki/Q171171","display_name":"Dermatology","level":1,"score":0.22436103224754333},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14046090841293335},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.07185319066047668},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icccnt51525.2021.9580174","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icccnt51525.2021.9580174","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 12th International Conference on Computing Communication and Networking Technologies (ICCCNT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1833156024","https://openalex.org/W1996000796","https://openalex.org/W2011327086","https://openalex.org/W2053584684","https://openalex.org/W2132964930","https://openalex.org/W2297722850","https://openalex.org/W2341528187","https://openalex.org/W2604184171","https://openalex.org/W2620219072","https://openalex.org/W2622332808","https://openalex.org/W2810511387","https://openalex.org/W2883255091","https://openalex.org/W2990356818","https://openalex.org/W3010754614","https://openalex.org/W3101998545","https://openalex.org/W3102348853","https://openalex.org/W4235411729","https://openalex.org/W6679791375"],"related_works":["https://openalex.org/W4226493464","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W2911497689","https://openalex.org/W2952813363","https://openalex.org/W4360783045","https://openalex.org/W2963346891","https://openalex.org/W2770149305","https://openalex.org/W2795259429"],"abstract_inverted_index":{"The":[0,37,133,153],"skin":[1,23,44,82,100,166],"spectrum":[2],"is":[3],"used":[4,121],"in":[5,58,162],"a":[6,95,126,147,174],"wide":[7],"range":[8],"of":[9,77,97,116,129,135,143,165,176],"studies":[10],"like":[11,65],"dermatology,":[12],"biometric":[13],"recognition,":[14],"cosmetic":[15,21,43],"research":[16],"and":[17,35,49,69,105,109,172,183],"disease":[18],"detection.":[19],"In":[20,72],"research,":[22],"can":[24],"be":[25],"classified":[26,106],"into":[27,107],"four":[28],"main":[29],"categories":[30],"as,":[31],"normal,":[32],"dry,":[33],"oily":[34,108,151],"combination.":[36],"current":[38],"methods":[39],"to":[40],"identify":[41],"the":[42,59,75,90,114,122,163],"type":[45,83,167],"are":[46],"time":[47],"consuming":[48],"error":[50,186],"prone.":[51],"Recently,":[52],"Deep":[53,157],"Learning":[54,158],"algorithms":[55],"have":[56,85,93,120],"been":[57,86],"limelight":[60],"for":[61,81],"various":[62],"classification":[63,84,138,168],"problems":[64],"text,":[66],"audio,":[67],"image":[68],"video":[70],"classifications.":[71],"this":[73],"paper,":[74],"applications":[76],"Convolutional":[78],"Neural":[79],"Network":[80],"studied.":[87],"To":[88,112],"train":[89],"model,":[91,118],"we":[92,119],"created":[94],"dataset":[96,175],"over":[98],"80":[99],"images,collected":[101],"by":[102],"web":[103],"scraping":[104],"dry":[110],"categories.":[111],"evaluate":[113],"performance":[115],"our":[117,136],"trained":[123],"model":[124,139],"on":[125],"small":[127],"sample":[128],"easily":[130],"distinguishable":[131],"images.":[132,152],"results":[134,154],"CNN":[137],"show":[140,155],"an":[141],"accuracy":[142],"about":[144],"85%":[145],"with":[146,173],"slight":[148],"bias":[149],"towards":[150],"that":[156],"has":[159],"great":[160],"potential":[161],"field":[164],"from":[169],"facial":[170],"images,":[171],"greater":[177],"size,":[178],"could":[179],"give":[180],"more":[181],"optimal":[182],"even":[184],"lesser":[185],"prone":[187],"results.":[188]},"counts_by_year":[{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2026-02-25T23:00:34.991745","created_date":"2025-10-10T00:00:00"}