506 citations
- Centre National de la Recherche ScientifiqueFR177 papers
- Institut de Mathématiques de BourgogneFR114 papers
- Laboratoire Interdisciplinaire Carnot de BourgogneFR93 papers
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19 papers · 1 filter
Revisit 1D Total Variation restoration problem with new real-time algorithms for signal and hyper-parameter estimations
Zhanhao Liu, Marion Perrodin, Thomas Chambrion +1
1D Total Variation (TV) denoising, considering the data fidelity and the Total Variation (TV) regularization, proposes a good restored signal preserving shape edges. The main issue…
Topological two-dimensional Su-Schrieffer-Heeger analogue acoustic networks: Total reflection at corners and corner induced modes
Antonin Coutant, Vassos Achilleos, Olivier Richoux +2
In this work, we investigate some aspects of an acoustic analogue of the two-dimensional Su-Schrieffer-Heeger model. The system is composed of alternating cross-section tubes conne…
Automatic Myocardial Infarction Evaluation from Delayed-Enhancement Cardiac MRI using Deep Convolutional Networks
Kibrom Berihu Girum, Youssef Skandarani, Raabid Hussain +3
In this paper, we propose a new deep learning framework for an automatic myocardial infarction evaluation from clinical information and delayed enhancement-MRI (DE-MRI). The propos…
SHARP 2020: The 1st Shape Recovery from Partial Textured 3D Scans Challenge Results
Alexandre Saint, Anis Kacem, Kseniya Cherenkova +7
The SHApe Recovery from Partial textured 3D scans challenge, SHARP 2020, is the first edition of a challenge fostering and benchmarking methods for recovering complete textured 3D…
Depth-Adapted CNN for RGB-D cameras
Zongwei Wu, Guillaume Allibert, Christophe Stolz +1
Conventional 2D Convolutional Neural Networks (CNN) extract features from an input image by applying linear filters. These filters compute the spatial coherence by weighting the ph…
Segmentation-free Estimation of Aortic Diameters from MRI Using Deep Learning
Axel Aguerreberry, Ezequiel de la Rosa, Alain Lalande +1
Accurate and reproducible measurements of the aortic diameters are crucial for the diagnosis of cardiovascular diseases and for therapeutic decision making. Currently, these measur…