2018
DOI: 10.14419/ijet.v7i4.6.20446
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Face Recognition Approaches: A Survey

Abstract: Face Recognition (FR) is a significant area in computer vision plus pattern recognition. The face is the easiest mode to discriminate the specific individuality of every other. FR is a particular identification scheme that usages particular features of an individual to recognize the individual's identity. The challenges in FR are aged, facial terms, variations in the imaging surroundings, illumination plus posture of the face. Specially, in this study firstly we mark an outline of FR that includes definition, … Show more

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Cited by 3 publications
(2 citation statements)
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“…PAN 2015 dataset contains tweets in English, Spanish, Italian and Dutch languages. This helps in identifying Age [21][22][23][24][25][26][27][28][29][30][31] Gender, language variety and personality type. PAN 2016 dataset contains tweets in English, Spanish and Dutch languages.…”
Section: Dataset Description and Metrics A Dataset Descriptionmentioning
confidence: 99%
“…PAN 2015 dataset contains tweets in English, Spanish, Italian and Dutch languages. This helps in identifying Age [21][22][23][24][25][26][27][28][29][30][31] Gender, language variety and personality type. PAN 2016 dataset contains tweets in English, Spanish and Dutch languages.…”
Section: Dataset Description and Metrics A Dataset Descriptionmentioning
confidence: 99%
“…Though it is developed for the sample discretization into various levels from the clusters, every model of deep learning is trained by the model on related discrete up to which five samples have been developed. Thus, the proposed big data exploits the key feature of the hierarchical oriented [15,[21][22] deep learning technique, known to be the BDHDLS, to organize the multiple criterion models [16][17][18][19][20]. This unique study makes the distribution of cluster adapted for the model that has been trained.…”
Section: Fig 2: Entries Based On Ranking For Multiple Criterion Decismentioning
confidence: 99%