FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2913152269> ?p ?o ?g. }

• W2913152269 endingPage "78" @default.
• W2913152269 startingPage "67" @default.
• W2913152269 abstract "To develop an automatic system that grades the severity of facial signs through 'selfies' pictures taken by women of different ages and ethnics.1140 women from three ethnics (African-American, Asian, Caucasian), of different ages (18-80 years old), took 'selfies' by high resolution smartphones cameras under different conditions of lighting or facial expressions. A dedicated software, was developed, based on a Convolutional Neural Network (CNN) that integrates training data from referential Skin Aging Atlases. The latter allows to an immediate quantification of the severity of nine facial signs according to the ethnicity declared by the subject. These automatic grading were confronted to those assessed by 12 trained experts and dermatologists either on 'selfies' pictures or in live conditions on a smaller cohort of women.The system appears weakly influenced by lighting conditions or facial expressions (coefficients of variations ranging 10-13% for most signs) and leads to global agreements with experts' assessments, even showing a better reproducibility on some facial signs.This automatic scoring system, still in development, seems offering a new quantitative approach in the quantified description of facial signs, independent from human vision, in many applications, being individual, cosmetic oriented or dermatological with regard to the follow-up of medical anti-ageing corrective strategies.De développer un système automatique qui quantifie la sévérité de certains signes du visage à partir de photographies de type ‘selfies’ pris par des femmes d'origine ethnique et d’âge différents. MÉTHODES: 1140 femmes de trois ethnies différentes (Afro-Américaines, Asiatiques, Caucasiennes), d’âges différents (18-80 ans) ont pris des selfies sous différentes conditions d’éclairage et d'expressions faciales. Un logiciel dédié a été développé, basé sur un réseau de convolution neuronal et intégrant les données d'annotations utilisant les Atlas de Vieillissement Cutané. Ce système quantifie immédiatement la sévérité de 9 signes faciaux selon l'ethnie déclarée par le sujet. Ces scores ont été confrontés à ceux de 12 experts et dermatologistes soit à partir des ‘selfies’ ou en conditions réelles sur un groupe plus restreint de femmes. RÉSULTATS: Le système apparaît faiblement influencé par les conditions d’éclairage et les expressions faciales (coefficients de variation de l'ordre de 10-13%) et conduit à des valeurs comparables de celles des experts, voire même de meilleure reproductibilité dans certains cas.Ce système de scorage automatique, encore en développement, semble offrir une nouvelle approche dans la description quantitative de signes du visage, indépendante de l’œil humain, dans de nombreuses applications, comme la personnalisation, à visée cosmétique ou dermatologique, dans le suivi de certaines stratégies médicales de l'antivieillissement cutané." @default.
• W2913152269 created "2019-02-21" @default.
• W2913152269 creator A5015689210 @default.
• W2913152269 creator A5022159821 @default.
• W2913152269 creator A5027171832 @default.
• W2913152269 creator A5029007864 @default.
• W2913152269 creator A5050384919 @default.
• W2913152269 creator A5061463635 @default.
• W2913152269 creator A5065107371 @default.
• W2913152269 creator A5067711103 @default.
• W2913152269 creator A5078891571 @default.
• W2913152269 creator A5087618971 @default.
• W2913152269 creator A5088482310 @default.
• W2913152269 creator A5089124970 @default.
• W2913152269 date "2019-02-01" @default.
• W2913152269 modified "2023-09-27" @default.
• W2913152269 title "A new procedure, free from human assessment that automatically grades some facial skin structural signs. Comparison with assessments by experts, using referential atlases of skin ageing" @default.
• W2913152269 cites W130327661 @default.
• W2913152269 cites W1972412827 @default.
• W2913152269 cites W1977050002 @default.
• W2913152269 cites W2000121859 @default.
• W2913152269 cites W2001367998 @default.
• W2913152269 cites W2007849936 @default.
• W2913152269 cites W2017164109 @default.
• W2913152269 cites W2018396727 @default.
• W2913152269 cites W2045031994 @default.
• W2913152269 cites W2045371114 @default.
• W2913152269 cites W2055015048 @default.
• W2913152269 cites W2066871669 @default.
• W2913152269 cites W2068715949 @default.
• W2913152269 cites W2070638289 @default.
• W2913152269 cites W2071041746 @default.
• W2913152269 cites W2079771822 @default.
• W2913152269 cites W2083846298 @default.
• W2913152269 cites W2106605311 @default.
• W2913152269 cites W2149515347 @default.
• W2913152269 cites W2153548469 @default.
• W2913152269 cites W2340338139 @default.
• W2913152269 cites W2524241816 @default.
• W2913152269 cites W2525975096 @default.
• W2913152269 cites W2528963741 @default.
• W2913152269 cites W2549328289 @default.
• W2913152269 cites W2598352650 @default.
• W2913152269 cites W2753907396 @default.
• W2913152269 cites W2887633820 @default.
• W2913152269 cites W2888838155 @default.
• W2913152269 cites W2890923548 @default.
• W2913152269 doi "https://doi.org/10.1111/ics.12512" @default.
• W2913152269 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30664236" @default.
• W2913152269 hasPublicationYear "2019" @default.
• W2913152269 type Work @default.
• W2913152269 sameAs 2913152269 @default.
• W2913152269 citedByCount "28" @default.
• W2913152269 countsByYear W29131522692019 @default.
• W2913152269 countsByYear W29131522692020 @default.
• W2913152269 countsByYear W29131522692021 @default.
• W2913152269 countsByYear W29131522692022 @default.
• W2913152269 countsByYear W29131522692023 @default.
• W2913152269 crossrefType "journal-article" @default.
• W2913152269 hasAuthorship W2913152269A5015689210 @default.
• W2913152269 hasAuthorship W2913152269A5022159821 @default.
• W2913152269 hasAuthorship W2913152269A5027171832 @default.
• W2913152269 hasAuthorship W2913152269A5029007864 @default.
• W2913152269 hasAuthorship W2913152269A5050384919 @default.
• W2913152269 hasAuthorship W2913152269A5061463635 @default.
• W2913152269 hasAuthorship W2913152269A5065107371 @default.
• W2913152269 hasAuthorship W2913152269A5067711103 @default.
• W2913152269 hasAuthorship W2913152269A5078891571 @default.
• W2913152269 hasAuthorship W2913152269A5087618971 @default.
• W2913152269 hasAuthorship W2913152269A5088482310 @default.
• W2913152269 hasAuthorship W2913152269A5089124970 @default.
• W2913152269 hasConcept C127413603 @default.
• W2913152269 hasConcept C142724271 @default.
• W2913152269 hasConcept C147176958 @default.
• W2913152269 hasConcept C154945302 @default.
• W2913152269 hasConcept C15744967 @default.
• W2913152269 hasConcept C195704467 @default.
• W2913152269 hasConcept C2777286243 @default.
• W2913152269 hasConcept C41008148 @default.
• W2913152269 hasConcept C71924100 @default.
• W2913152269 hasConcept C72563966 @default.
• W2913152269 hasConceptScore W2913152269C127413603 @default.
• W2913152269 hasConceptScore W2913152269C142724271 @default.
• W2913152269 hasConceptScore W2913152269C147176958 @default.
• W2913152269 hasConceptScore W2913152269C154945302 @default.
• W2913152269 hasConceptScore W2913152269C15744967 @default.
• W2913152269 hasConceptScore W2913152269C195704467 @default.
• W2913152269 hasConceptScore W2913152269C2777286243 @default.
• W2913152269 hasConceptScore W2913152269C41008148 @default.
• W2913152269 hasConceptScore W2913152269C71924100 @default.
• W2913152269 hasConceptScore W2913152269C72563966 @default.
• W2913152269 hasIssue "1" @default.
• W2913152269 hasLocation W29131522691 @default.
• W2913152269 hasLocation W29131522692 @default.
• W2913152269 hasOpenAccess W2913152269 @default.
• W2913152269 hasPrimaryLocation W29131522691 @default.
• W2913152269 hasRelatedWork W2030114605 @default.
• W2913152269 hasRelatedWork W2041777094 @default.

• next