Ce cours vous apprendra à créer des réseaux neuronaux convolutifs et à les appliquer aux données d'image. Grâce à l'apprentissage en profondeur, la vision par ordinateur fonctionne beaucoup mieux qu'il y a seulement deux ans, ce qui permet de nombreuses applications passionnantes allant de la conduite autonome en toute sécurité, à la reconnaissance faciale précise, à la lecture automatique des images radiologiques.
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There are 4 modules in this course
Apprendre à mettre en œuvre les couches de base des CNN (mise en commun, convolutions) et à les empiler correctement dans un réseau profond pour résoudre les problèmes de classification d'images multi-classes.
What's included
12 videos4 readings1 assignment2 programming assignments2 ungraded labs
Découvrir les astuces pratiques et les méthodes utilisées dans les CNN profonds directement à partir des articles de recherche.
What's included
11 videos1 reading1 assignment1 programming assignment2 ungraded labs
Apprendre à appliquer vos connaissances des CNN à l'un des domaines les plus difficiles mais les plus sensibles de la vision par ordinateur : Détection d’objets.
What's included
10 videos2 readings1 assignment1 programming assignment1 ungraded lab
Découvrez comment les CNN peuvent être appliqués à plusieurs domaines, y compris la génération d'art et la reconnaissance faciale. Mettez en œuvre votre propre algorithme pour générer de l'art et reconnaître les visages !
What's included
11 videos3 readings1 assignment2 programming assignments2 ungraded labs
Offered by
Recommended if you're interested in Machine Learning
Imperial College London
Coursera Project Network
University of Geneva
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