{"id":"https://openalex.org/W4388901737","doi":"https://doi.org/10.1109/tencon58879.2023.10322396","title":"Enhancing Facial Expression Synthesis through GAN with Multi-Scale Dilated Feature Extraction and Edge-Enhanced Facial Features<sup>*</sup>","display_name":"Enhancing Facial Expression Synthesis through GAN with Multi-Scale Dilated Feature Extraction and Edge-Enhanced Facial Features<sup>*</sup>","publication_year":2023,"publication_date":"2023-10-31","ids":{"openalex":"https://openalex.org/W4388901737","doi":"https://doi.org/10.1109/tencon58879.2023.10322396"},"language":"en","primary_location":{"id":"doi:10.1109/tencon58879.2023.10322396","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/tencon58879.2023.10322396","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TENCON 2023 - 2023 IEEE Region 10 Conference (TENCON)","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/A5071463553","display_name":"U. Nimitha","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nimitha. U","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093315907","display_name":"P Gunasagar","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"P Gunasagar","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091398394","display_name":"VVSS Durgaprasad","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"VVSS Durgaprasad","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093315908","display_name":"Abhijith KS","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Abhijith KS","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"RVV Manikantha Sai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"RVV Manikantha Sai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5070801589","display_name":"Ameer PM","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ameer PM","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1123,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.42787528,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"47","last_page":"52"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9998000264167786,"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":0.9998000264167786,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9977999925613403,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9954000115394592,"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/computer-science","display_name":"Computer science","score":0.8030107617378235},{"id":"https://openalex.org/keywords/facial-expression","display_name":"Facial expression","score":0.6793334484100342},{"id":"https://openalex.org/keywords/sadness","display_name":"Sadness","score":0.6616381406784058},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6552722454071045},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5760028958320618},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5643455982208252},{"id":"https://openalex.org/keywords/disgust","display_name":"Disgust","score":0.5598418712615967},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5262227058410645},{"id":"https://openalex.org/keywords/emotion-classification","display_name":"Emotion classification","score":0.4974086582660675},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4420643746852875},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4246503412723541},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3376566171646118},{"id":"https://openalex.org/keywords/anger","display_name":"Anger","score":0.18253889679908752}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8030107617378235},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.6793334484100342},{"id":"https://openalex.org/C2779812673","wikidata":"https://www.wikidata.org/wiki/Q169251","display_name":"Sadness","level":3,"score":0.6616381406784058},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6552722454071045},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5760028958320618},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5643455982208252},{"id":"https://openalex.org/C2777375102","wikidata":"https://www.wikidata.org/wiki/Q208351","display_name":"Disgust","level":3,"score":0.5598418712615967},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5262227058410645},{"id":"https://openalex.org/C206310091","wikidata":"https://www.wikidata.org/wiki/Q750859","display_name":"Emotion classification","level":2,"score":0.4974086582660675},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4420643746852875},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4246503412723541},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3376566171646118},{"id":"https://openalex.org/C2779302386","wikidata":"https://www.wikidata.org/wiki/Q79871","display_name":"Anger","level":2,"score":0.18253889679908752},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tencon58879.2023.10322396","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/tencon58879.2023.10322396","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TENCON 2023 - 2023 IEEE Region 10 Conference (TENCON)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1579590535","https://openalex.org/W1878727728","https://openalex.org/W1964988170","https://openalex.org/W2098693229","https://openalex.org/W2125389028","https://openalex.org/W2156531583","https://openalex.org/W2290075282","https://openalex.org/W2325939864","https://openalex.org/W2559655401","https://openalex.org/W2754447548","https://openalex.org/W2787512630","https://openalex.org/W2807869636","https://openalex.org/W2884954981","https://openalex.org/W2911641177","https://openalex.org/W2944614370","https://openalex.org/W2964859579","https://openalex.org/W3034751874","https://openalex.org/W3035575271","https://openalex.org/W3085051361","https://openalex.org/W4213297113","https://openalex.org/W4297371017","https://openalex.org/W6678815747","https://openalex.org/W6685777803","https://openalex.org/W6748883595","https://openalex.org/W6780248173"],"related_works":["https://openalex.org/W4238520549","https://openalex.org/W3216173459","https://openalex.org/W2794357331","https://openalex.org/W4242611441","https://openalex.org/W4242034606","https://openalex.org/W4250499761","https://openalex.org/W2037174948","https://openalex.org/W1991697485","https://openalex.org/W2519456985","https://openalex.org/W1761974557"],"abstract_inverted_index":{"Affective":[0],"computing":[1,13],"aims":[2],"to":[3,27,95,121],"facilitate":[4],"effective":[5],"communication":[6],"between":[7],"humans":[8],"and":[9,25,65,101,132,149,167,192],"machines.":[10],"Many":[11],"affective":[12],"systems":[14],"use":[15],"machine":[16],"learning":[17],"models":[18],"trained":[19],"on":[20],"labeled":[21],"data,":[22],"like":[23],"images":[24],"videos,":[26],"recognize":[28],"emotions.":[29],"Among":[30],"these,":[31],"the":[32,51,63,97,107,118,123,168,182,186],"Generative":[33],"Adversarial":[34],"Network":[35,156],"(GAN)-based":[36],"expression":[37,127,158],"GAN":[38],"(ExprGAN)":[39],"stands":[40],"out":[41],"as":[42,62],"it":[43],"can":[44,137,197],"generate":[45,138],"faces":[46,53,139],"displaying":[47],"various":[48],"expressions.":[49,73],"However,":[50],"generated":[52],"often":[54],"lack":[55],"clarity":[56],"in":[57],"crucial":[58],"facial":[59,72,104,108,126],"features,":[60,128],"such":[61],"eyes":[64],"lips,":[66],"which":[67,196],"are":[68,174],"essential":[69],"for":[70,176,200],"defining":[71],"To":[74,151],"address":[75],"this":[76],"issue,":[77],"a":[78,153,160],"novel":[79],"feature":[80],"extraction":[81],"block":[82],"is":[83,115],"proposed.":[84],"This":[85],"module":[86],"incorporates":[87],"two":[88],"parallel":[89],"channels":[90],"with":[91,140],"multi-scale":[92,103],"dilated":[93],"convolution":[94],"mimic":[96],"human":[98],"visual":[99],"system":[100],"extract":[102],"features":[105],"from":[106],"images.":[109],"Additionally,":[110],"an":[111],"unsharp":[112],"masking":[113],"filter":[114],"integrated":[116],"into":[117],"pre-processing":[119],"stage":[120],"enhance":[122],"quality":[124,191],"of":[125],"making":[129],"them":[130],"sharper":[131],"clearer.":[133],"The":[134,178],"proposed":[135,183],"model":[136,184],"six":[141],"distinct":[142],"expressions:":[143],"Anger,":[144],"Disgust,":[145],"Fear,":[146],"Happiness,":[147],"Sadness,":[148],"Surprise.":[150],"evaluate,":[152],"Convolutional":[154],"Neural":[155],"(CNN)-based":[157],"classifier,":[159,166],"Principal":[161],"Component":[162],"Analysis":[163],"(PCA)-based":[164],"face":[165],"FID":[169],"(Frechet":[170],"Inception":[171],"Distance)":[172],"score":[173],"used":[175],"comparison.":[177],"results":[179],"demonstrate":[180],"that":[181],"outperforms":[185],"existing":[187],"ExprGAN,":[188],"providing":[189],"better":[190],"more":[193],"expressive":[194],"faces,":[195],"be":[198],"beneficial":[199],"improving":[201],"human-machine":[202],"interaction.":[203]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
