A review on gender identification using machine learning based on fingerprints

2019 ◽  
Vol 40 (5) ◽  
pp. 1121-1129 ◽  
Author(s):  
Jitendra Singh Yadav ◽  
Amit Kumar Gupta ◽  
Arjit Saxena
2020 ◽  
pp. 57-63
Author(s):  
admin admin ◽  
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The human facial emotions recognition has attracted interest in the field of Artificial Intelligence. The emotions on a human face depicts what’s going on inside the mind. Facial expression recognition is the part of Facial recognition which is gaining more importance and need for it increases tremendously. Though there are methods to identify expressions using machine learning and Artificial Intelligence techniques, this work attempts to use convolution neural networks to recognize expressions and classify the expressions into 6 emotions categories. Various datasets are investigated and explored for training expression recognition models are explained in this paper and the models which are used in this paper are VGG 19 and RESSNET 18. We included facial emotional recognition with gender identification also. In this project we have used fer2013 and ck+ dataset and ultimately achieved 73% and 94% around accuracies respectively.


2018 ◽  
Vol 123 ◽  
pp. 417-423 ◽  
Author(s):  
Alexander Sboev ◽  
Ivan Moloshnikov ◽  
Dmitry Gudovskikh ◽  
Anton Selivanov ◽  
Roman Rybka ◽  
...  

2018 ◽  
Vol 123 ◽  
pp. 424-431 ◽  
Author(s):  
Alexander Sboev ◽  
Ivan Moloshnikov ◽  
Dmitry Gudovskikh ◽  
Anton Selivanov ◽  
Roman Rybka ◽  
...  

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