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List of results
- Random rational expression generation + (boillod.16.seminar)
- Génération aléatoire d'expression rationnelle + (boillod.16.seminar)
- Text extraction method based on wavelets + (boissel.12.seminar)
- Extraction de texte avec des ondelettes + (boissel.12.seminar)
- Reduce the resource consumption of a complex image processing chain + (boissel.13.seminar)
- Réduire les ressources utilisées par une chaîne de traitement d'images complexe + (boissel.13.seminar)
- Using a wavelet-based descriptor to extract information on object shape + (boissel.13.seminar2)
- Utilisation d'un descripteur à base de transformée en ondelettes pour extraire des informations sur la forme des objets + (boissel.13.seminar2)
- A Formally-Proved Algorithm to Compute the Correct Average of Decimal Floating-Point Numbers + (boldo.18.arith)
- C-Transformers — A Framework to Write C Program Transformations + (borghi.06.crossroads)
- MITLL 2012 Speaker Recognition Evaluation System Description + (borgstrom.12.nistsre)
- Learning Diversity Attributes in Multi-Session Recommendations + (bouarour.22.ieeebigdata)
- Boltzmann Machine in speaker verification + (bounthong.13.seminar)
- Les Machines de Boltzmann dans la reconnaissance du locuteur + (bounthong.13.seminar)
- Speaker specific i-vector channel compensation in speaker recognition + (bounthong.15.seminar)
- Compensation d'i-vecteur spécifique aux locuteurs dans la reconnaissance du locuteur + (bounthong.15.seminar)
- On Making nD Images Well-Composed by a Self-Dual Local Interpolation + (boutry.14.dgci)
- Une généralisation du bien-composé à la dimension n + (boutry.14.geodis)
- How to Make nD Images Well-Composed Without Interpolation + (boutry.15.icip)
- How to Make nD Functions Digitally Well-Composed in a Self-Dual Way + (boutry.15.ismm)
- A Study of Well-Composedness in n-D + (boutry.16.phd)
- Well-Composedness in Alexandrov spaces implies Digital Well-Composedness in Z^n + (boutry.17.dgci)
- A Tutorial on Well-Composedness + (boutry.17.jmiv)
- Weakly Well-Composed Cell Complexes over nD Pictures + (boutry.18.is)
- One More Step Towards Well-Composedness of Cell Complexes over n-D Pictures + (boutry.19.dgci)
- An Equivalence Relation between Morphological Dynamics and Persistent Homology in 1D + (boutry.19.ismm)
- How to Make n-D Plain Maps Alexandrov-Well-Composed in a Self-dual Way + (boutry.19.jmiv)
- Using Separated Inputs for Multimodal Brain Tumor Segmentation with 3D U-Net-like Architectures + (boutry.20.brainles)
- A translational pathway of deep learning methods in Gastro-Intestinal Endoscopy + (boutry.20.endocv)
- Euler Well-Composedness + (boutry.20.iwcia1)
- A 4D Counter-Example Showing that DWCness Does Not Imply CWCness in n-D + (boutry.20.iwcia2)
- Topological Properties of the First Non-Local Digitally Well-Composed Interpolation on n-D Cubical Grids + (boutry.20.jmiv.1)
- Equivalence between Digital Well-Composedness and Well-Composedness in the Sense of Alexandrov on n-D Cubical Grids + (boutry.20.jmiv.2)
- An Equivalence Relation between Morphological Dynamics and Persistent Homology in n-D + (boutry.21.dgmm.1)
- A New Matching Algorithm between Trees of Shapes and its Application to Brain Tumor Segmentation + (boutry.21.dgmm.2)
- Stability of the Tree of Shapes to Additive Noise + (boutry.21.dgmm.3)
- Continuous Well-Composedness implies Digital Well-Composedness in n-D + (boutry.21.jmiv)
- Strong Euler Wellcomposedness + (boutry.21.joco)
- Deep Learning for Detection and Segmentation of Artefact and Disease Instances in Gastrointestinal Endoscopy + (boutry.21.media)
- Residual 3D U-Net with Localization for Brain Tumor Segmentation + (boutry.21.miccai)
- Gradient Vector Fields of Discrete Morse Functions and Watershed-Cuts + (boutry.22.dgmm)
- Some Equivalence Relation between Persistent Homology and Morphological Dynamics + (boutry.22.jmiv.2)
- Discrete Morse Functions and Watersheds + (boutry.23.jmiv)
- Two Stages CNN-Based Segmentation of GliomasUncertainty Quantification and Prediction of Overall Patient Survival + (buatois.19.brainles)
- Brain Tumor Segmentation with deep convolutional network approach + (buatois.19.seminar)
- Segmentation de tumeur cérébrale par réseau de neurones convolutionel + (buatois.19.seminar)
- Smart and robust segmentation of medical images using neural networks + (buatois.20.seminar)
- Segmentation robuste et intelligente d'images médicales par réseau de neurones + (buatois.20.seminar)
- Smart and robust segmentation of medical images using neural networks + (buatois.21.seminar)
- Segmentation robuste et intelligente d'images médicales par réseau de neurones + (buatois.21.seminar)
- A static C++ object-oriented programming (SCOOP) paradigm mixing benefits of traditional OOP and generic programming + (burrus.03.mpool)