Matches in SemOpenAlex for { <https://semopenalex.org/work/W3201556123> ?p ?o ?g. }
Showing items 1 to 72 of
72
with 100 items per page.
- W3201556123 endingPage "6675" @default.
- W3201556123 startingPage "6665" @default.
- W3201556123 abstract "In the modern days, the growth of online social networking websites and social media leads to an increasing adoption of computer-aided image recognition systems that automatically recognize and classify human subjects. One such familiar one is the anthropometric analysis of the human face that performs craniofacial plastic and reconstructive surgeries. To analyze the impact on facial anthropometrics, it is also essential to consider various factors such as age, gender, ethnicity, socioeconomic status, environment, and region. The repair and reconstruction of facial deformities to find the anatomical dimensions of the facial structures as used by plastic surgeons for their surgeries result from the physical or facial appearance of an individual. Gender classification plays an important role of identifying the person as either male or female using biometric images. The main goal is to interact with the system, so that gender differences are produced effectively and accurately. Hence, it is essential to select the features optimally to achieve better accuracy. Data mining or machine learning techniques can be useful to infer properties such as the gender or age of the people involved to analyze the human activities. Towards this end, the proposed work focuses on gender recognition thereby building a model to scan the eye image of a patient and determine if the gender of the patient is either male or female by applying deep learning methods. It is identified from the work that deep learning network yields a better performance for gender based classification based on the morphometry of eyes." @default.
- W3201556123 created "2021-09-27" @default.
- W3201556123 creator A5003119506 @default.
- W3201556123 creator A5029112155 @default.
- W3201556123 date "2022-04-24" @default.
- W3201556123 modified "2023-09-24" @default.
- W3201556123 title "Gender Prediction Based on Morphometry of Eyes Using Deep Learning Models" @default.
- W3201556123 cites W2320355672 @default.
- W3201556123 cites W3170516537 @default.
- W3201556123 cites W3172509895 @default.
- W3201556123 doi "https://doi.org/10.1149/10701.6665ecst" @default.
- W3201556123 hasPublicationYear "2022" @default.
- W3201556123 type Work @default.
- W3201556123 sameAs 3201556123 @default.
- W3201556123 citedByCount "1" @default.
- W3201556123 countsByYear W32015561232023 @default.
- W3201556123 crossrefType "journal-article" @default.
- W3201556123 hasAuthorship W3201556123A5003119506 @default.
- W3201556123 hasAuthorship W3201556123A5029112155 @default.
- W3201556123 hasConcept C108583219 @default.
- W3201556123 hasConcept C119857082 @default.
- W3201556123 hasConcept C126322002 @default.
- W3201556123 hasConcept C130537919 @default.
- W3201556123 hasConcept C138496976 @default.
- W3201556123 hasConcept C144024400 @default.
- W3201556123 hasConcept C153180895 @default.
- W3201556123 hasConcept C154945302 @default.
- W3201556123 hasConcept C15744967 @default.
- W3201556123 hasConcept C184297639 @default.
- W3201556123 hasConcept C2779304628 @default.
- W3201556123 hasConcept C31510193 @default.
- W3201556123 hasConcept C36289849 @default.
- W3201556123 hasConcept C41008148 @default.
- W3201556123 hasConcept C61427482 @default.
- W3201556123 hasConcept C71924100 @default.
- W3201556123 hasConceptScore W3201556123C108583219 @default.
- W3201556123 hasConceptScore W3201556123C119857082 @default.
- W3201556123 hasConceptScore W3201556123C126322002 @default.
- W3201556123 hasConceptScore W3201556123C130537919 @default.
- W3201556123 hasConceptScore W3201556123C138496976 @default.
- W3201556123 hasConceptScore W3201556123C144024400 @default.
- W3201556123 hasConceptScore W3201556123C153180895 @default.
- W3201556123 hasConceptScore W3201556123C154945302 @default.
- W3201556123 hasConceptScore W3201556123C15744967 @default.
- W3201556123 hasConceptScore W3201556123C184297639 @default.
- W3201556123 hasConceptScore W3201556123C2779304628 @default.
- W3201556123 hasConceptScore W3201556123C31510193 @default.
- W3201556123 hasConceptScore W3201556123C36289849 @default.
- W3201556123 hasConceptScore W3201556123C41008148 @default.
- W3201556123 hasConceptScore W3201556123C61427482 @default.
- W3201556123 hasConceptScore W3201556123C71924100 @default.
- W3201556123 hasIssue "1" @default.
- W3201556123 hasLocation W32015561231 @default.
- W3201556123 hasOpenAccess W3201556123 @default.
- W3201556123 hasPrimaryLocation W32015561231 @default.
- W3201556123 hasRelatedWork W2887663052 @default.
- W3201556123 hasRelatedWork W2899781844 @default.
- W3201556123 hasRelatedWork W2987988558 @default.
- W3201556123 hasRelatedWork W2992524653 @default.
- W3201556123 hasRelatedWork W3005720838 @default.
- W3201556123 hasRelatedWork W3024094383 @default.
- W3201556123 hasRelatedWork W4223943233 @default.
- W3201556123 hasRelatedWork W4292622079 @default.
- W3201556123 hasRelatedWork W4312200629 @default.
- W3201556123 hasRelatedWork W4378192005 @default.
- W3201556123 hasVolume "107" @default.
- W3201556123 isParatext "false" @default.
- W3201556123 isRetracted "false" @default.
- W3201556123 magId "3201556123" @default.
- W3201556123 workType "article" @default.