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Publications

Publications depuis 2008

Vous pouvez retrouver les publications du laboratoire depuis 2008 sur le site des archives ouvertes du CNRS, et utiliser le moteur de recherche pour accéder à une publication particulière (onglets "Consultation" ou "Recherche simple").

Les publications des équipes depuis 2008 peuvent être également consultées à partir des liens suivants :

Publications antérieures à 2008

Les publications plus anciennes se trouvent à cette adresse.

Nos dix dernières publications

[hal-01835422] A neural network algorithm for detection of GI angiectasia during small-bowel capsule endoscopy

Background and Aims Gastrointestinal angiectasia (GIA) is the most common small bowel (SB) vascular lesion, with an inherent risk of bleeding. SB Capsule Endoscopy (SB-CE) is the currently accepted diagnostic procedure. The aim of this study was to develop a computer-assisted diagnosis (CAD) tool for the detection of GIA. [...]

[hal-01822769] Impact de la scénarisation des séquences d'une classe inversée hybride sur l'engagement des étudiants en licence scientifique

Depuis 3 ans à l'université de Cergy-Pontoise, nous adoptons un dispositif d'enseignement hybride en classe inversée de type SPOC sur des modules de formation en informatique. Sur plusieurs cohortes de 60 à 350 étudiants de différents niveaux (L1, L2, L3) ou type de filière (en initial ou professionnalisation), nous avons pu tester et observer les effets des activités préalables à la séquence d'enseignement, du contrat pédagogique présenté à l'étudiant, de la mise en place de routine dans les séances, de l'enchaînement des évaluations formatives et sommatives et de l'encadrement des enseignants chargés d'assurer les TD. [...]

[hal-01822776] Rêver son chemin pour le réussir : construire son portfolio pour atteindre ses objectifs de vie

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[hal-01820489] Jigsaw Puzzle Solving Using Local Feature Co-occurrences In Deep Neural Networks

Archaeologists are in dire need of automated object reconstruction methods. Fragments reassembly is close to puzzle problems, which may be solved by computer vision algorithms. As they are often beaten on most image related tasks by deep learning algorithms, we study a classification method that can solve jigsaw puzzles. [...]

[hal-01829258] An interior Compton Scatter Tomography

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[hal-01815707] Multimodal Deep Neural Networks for Pose Estimation and Action Recognition

In this work, we present a unified multimodal neural network for pose estimation from RGB images and action recognition from video sequences. We show that a multimodal approach benefits 3D pose estimation by mixing high precision 3D data and “in the wild” 2D annotated images, while action recognition also benefits from better visual features. [...]

[hal-01826354] Kriging-based spatial interpolation from measurements for sound level mapping in urban areas

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[hal-01822537] Synergistic control of a multi-segments vertebral column robot based on tensegrity for postural balance

We present a neuronal architecture to control a compliant robotic model of the human vertebral column for postural balance. The robotic structure is designed using the principle of tensegrity that ensures to be lightweight, auto-replicative with multi-degrees of freedom, flexible and also robust to perturbations. [...]

[hal-01815703] 2D/3D Pose Estimation and Action Recognition using Multitask Deep Learning

Action recognition and human pose estimation are closely related but both problems are generally handled as distinct tasks in the literature. In this work, we propose a multitask framework for jointly 2D and 3D pose estimation from still images and human action recognition from video sequences. [...]

[hal-01816918] Leveraging Implicit Spatial Information In Global Features For Image Retrieval

Most image retrieval methods use global features that aggregate local distinctive patterns into a single representation. However, the aggregation process destroys the relative spatial information by considering orderless sets of local descriptors. We propose to integrate relative spatial information into the aggregation process by taking into account co-occurrences of local patterns in a tensor framework. [...]