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pro vyhledávání: '"Fortun, Denis"'
Autor:
Eloy, Thibaut, Baudrier, Etienne, Laporte, Marine, Hamel, Virginie, Guichard, Paul, Fortun, Denis
Single particle reconstruction has recently emerged in 3D fluorescence microscopy as a powerful technique to improve the axial resolution and the degree of fluorescent labeling. It is based on the reconstruction of an average volume of a biological p
Externí odkaz:
http://arxiv.org/abs/2301.09452
In this paper, we address the problem of registering multiple point clouds corrupted with high anisotropic localization noise. Our approach follows the widely used framework of Gaussian mixture model (GMM) reconstruction with an expectation-maximizat
Externí odkaz:
http://arxiv.org/abs/2201.00708
Current algorithmic approaches for piecewise affine motion estimation are based on alternating motion segmentation and estimation. We propose a new method to estimate piecewise affine motion fields directly without intermediate segmentation. To this
Externí odkaz:
http://arxiv.org/abs/1802.01872
Autor:
Fortun, Denis
Nous nous intéressons dans cette thèse au problème de l'estimation dense du mouvement dans des séquences d'images, également désigné sous le terme de flot optique. Les approches usuelles exploitent une paramétrisation locale ou une régularis
Externí odkaz:
http://www.theses.fr/2014REN1S093/document
Handling all together large displacements, motion details and occlusions remains an open issue for reliable computation of optical flow in a video sequence. We propose a two-step aggregation paradigm to address this problem. The idea is to supply loc
Externí odkaz:
http://arxiv.org/abs/1407.5759
Akademický článek
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Publikováno v:
In Computer Vision and Image Understanding April 2016 145:81-94
Publikováno v:
In Computer Vision and Image Understanding May 2015 134:1-21
Publikováno v:
Frontiers in Neuroimaging
Frontiers in Neuroimaging, 2022, 1, pp.1008128. ⟨10.3389/fnimg.2022.1008128⟩
Frontiers in Neuroimaging, 2022, 1, pp.1008128. ⟨10.3389/fnimg.2022.1008128⟩
Registration is a crucial step in the design of automatic change detection methods dedicated to longitudinal brain MRI. Even small registration inaccuracies can significantly deteriorate the detection performance by introducing numerous spurious dete
Publikováno v:
GRETSI 22, XXVIIIème Colloque Francophone de Traitement du Signal et des Images, Nancy, 06-09 Septembre 2022
GRETSI 22, XXVIIIème Colloque Francophone de Traitement du Signal et des Images, Nancy, 06-09 Septembre 2022, Sep 2022, Nancy, France
GRETSI 22, XXVIIIème Colloque Francophone de Traitement du Signal et des Images, Nancy, 06-09 Septembre 2022, Sep 2022, Nancy, France
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______165::0247103914895407f9b92b2ee322e227
https://hal.science/hal-03806705
https://hal.science/hal-03806705