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Development of video-based emotion recognition using deep learning with Google Colab

[...]frames are to be extracted from the input video [4]. Face detection Emotions are featured mainly from the face. [...]it is crucial to detect the face to obtain facial features for further processing and recognition. [...]resizing is very important to shorten the processing time. [...]better res...

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Published in:Telkomnika 2020-10, Vol.18 (5), p.2463-2471
Main Authors: Gunawan, Teddy Surya, Ashraf, Arselan, Riza, Bob Subhan, Haryanto, Edy Victor, Rosnelly, Rika, Kartiwi, Mira, Janin, Zuriati
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container_end_page 2471
container_issue 5
container_start_page 2463
container_title Telkomnika
container_volume 18
creator Gunawan, Teddy Surya
Ashraf, Arselan
Riza, Bob Subhan
Haryanto, Edy Victor
Rosnelly, Rika
Kartiwi, Mira
Janin, Zuriati
description [...]frames are to be extracted from the input video [4]. Face detection Emotions are featured mainly from the face. [...]it is crucial to detect the face to obtain facial features for further processing and recognition. [...]resizing is very important to shorten the processing time. [...]better resizing techniques should be used to preserve image attributes after resizing [8]. The accuracy of the classification depends on whether the features are well representing the expression or not. [...]the optimization of the selected features will automatically improve classification accuracy [9].
doi_str_mv 10.12928/telkomnika.v18i5.16717
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subjects Accuracy
Algorithms
Architecture
Artificial intelligence
Deep learning
Emotions
Face recognition
Human-computer interaction
Image classification
Machine learning
Neural networks
Optimization
Researchers
title Development of video-based emotion recognition using deep learning with Google Colab
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