.. .. Vue-d'ensemble-des-traitements,

.. .. Résultats-globaux,

.. .. Conclusion??,

?. Etat-de-l'art,

.. .. Activités-de-premier-niveau,

.. .. Statistiques,

. ?. Pré-analyse-du-corpus,

, Processus de classification des activités physiques

?. .. Activités-physiques-de-deuxième-niveau,

?. .. Résultats,

, Activités physiques de troisième niveau : détection de l'attention envers la TV ??

, Limites des études effectuées dans les chapitres

.. .. Conclusion?,

, Vue d'ensemble de la DST pour la reconnaissance de l'activité

. .. Conclusion???????????????,

, Etude de la séléction de descripteurs pour l'apprentissage en profondeur, p.154

, Etude de l'optimisation de l'entrainement du modèle CNN-brutes??, p.157

. ?. L'architecture-proposée, . ??, and . ?????????????????????, , p.158

. Résultats and . .. ??,

.. .. Conclusion?,

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;. Ainsi and . Hammerla, nos résultats sont comparables à l'état de l'art, notamment les travaux de, p.189, 2016.

A. , En effet, contrairement aux méthodes précédentes, cette approche a beaucoup moins d'hyper-paramètres à ajuster, ce qui peut être avantageux pour la vitesse de convergence mais aussi, en l'appliquant directement sur la couche de décision, celle-ci verra sa performance de classification améliorée