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Crying emotion classification, using machine learning algorithms - Nouha Azouzi

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2019-02-15
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We are witnessing the birth of a new era in which almost every object can be a connected object. In recent years, the internet of things field attracts many researchers¿ attention. Subsequently, the number of internet of things application is augmenting quickly. Furthermore, on the other hand, face detection and emotion recognition have been an active research area for several years, and therefore a large a ... Visas aprašymas

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We are witnessing the birth of a new era in which almost every object can be a connected object. In recent years, the internet of things field attracts many researchers¿ attention. Subsequently, the number of internet of things application is augmenting quickly. Furthermore, on the other hand, face detection and emotion recognition have been an active research area for several years, and therefore a large amount of work has been done in this field. Our aim is to create a system able to help parent while raising their baby. This system is equipped with an intelligent camera that performs an automated facial expression analysis in order to detect a child crying. In general, three main steps can be presented within exploring the facial expression analysis problem. First, in order to analyze a facial expression, a face need to be detected in a scene. Then, a mechanism is used, to execute the extraction of the facial expression information from the presented image or image sequence. Followed by the final step which is facial expression classification.

Daugiau informacijos

Autorius Nouha Azouzi
Leidėjas Éditions universitaires européennes
Išleidimo metai 2019
Viršelio tipas Minkšti viršeliai
EAN 9786138459859
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59,27 € 79,02 €