2020
DOI: 10.1016/j.matpr.2020.08.350
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Gender and age prediction from real time facial images using CNN

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Cited by 26 publications
(15 citation statements)
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“…This step aims to initialize randomly the real population that contains N objects using Eq. (18). Also, each object is characterized by their density (D i ) , volume (V i ) and acceleration (Γ i ) which are defined in random way using the following equations Eq.…”
Section: Archimedes Optimization Algorithm (Aoa)mentioning
confidence: 99%
See 1 more Smart Citation
“…This step aims to initialize randomly the real population that contains N objects using Eq. (18). Also, each object is characterized by their density (D i ) , volume (V i ) and acceleration (Γ i ) which are defined in random way using the following equations Eq.…”
Section: Archimedes Optimization Algorithm (Aoa)mentioning
confidence: 99%
“…Nowadays, deep learned features are used exponentially in machine learning, especially in computer vision [9], biomedical application [10,11] and remote sensing [12,13]. Recently, several architecture are created by pretrained CNN such as VGG16, ResNet, GoogleNet and CaffeNet for gender recognition [14,15,16,17,18], AlexNet [19], Inception [20]. Furthermore, a comparative study between several pretrained CNN asuch s MobileNet, DensNet, Xception and SqueezeNet is realized by [21] for gender recognition.…”
Section: Introductionmentioning
confidence: 99%
“…Gender prediction models are widely used across different domains such as advertising, security and human–computer interaction. Similar to [ 2 , 6 , 19 , 26 , 36 , 37 , 58 , 77 ], we focus on gender prediction from facial images. Some of these works [ 2 , 19 , 26 , 36 , 58 ] proposed the use of CNN models to predict the gender.…”
Section: Related Workmentioning
confidence: 99%
“…Similar to [ 2 , 6 , 19 , 26 , 36 , 37 , 58 , 77 ], we focus on gender prediction from facial images. Some of these works [ 2 , 19 , 26 , 36 , 58 ] proposed the use of CNN models to predict the gender. Abirami et al [ 2 ] used a CNN model to jointly predict the gender and the age of a person from facial images.…”
Section: Related Workmentioning
confidence: 99%
See 1 more Smart Citation