291 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- École Nationale Supérieure des Mines de ParisFR12 papers
- Université Paris Sciences et LettresFR8 papers
- Centre National de la Recherche ScientifiqueFR5 papers
- Observatoire de ParisFR5 papers
- Laboratoire d’Etudes du Rayonnement et de la Matière en Astrophysique et AtmosphèresFR4 papers
- Sorbonne UniversitéFR4 papers
- Université Paris DiderotFR4 papers
- Commissariat à l'Énergie Atomique et aux Énergies AlternativesFR3 papers
- Galaxies, Etoiles, Physique et InstrumentationFR3 papers
- Space Telescope Science InstituteUS3 papers
- University of California, Santa CruzUS3 papers
- University of PennsylvaniaUS3 papers
18 papers
Adapting the Hypersphere Loss Function from Anomaly Detection to Anomaly Segmentation
Joao P. C. Bertoldo, Santiago Velasco-Forero, Jesus Angulo +1
We propose an incremental improvement to Fully Convolutional Data Description (FCDD), an adaptation of the one-class classification approach from anomaly detection to image anomaly…
[Reproducibility Report] Explainable Deep One-Class Classification
Joao P. C. Bertoldo, Etienne Decencière
Fully Convolutional Data Description (FCDD), an explainable version of the Hypersphere Classifier (HSC), directly addresses image anomaly detection (AD) and pixel-wise AD without a…
Paris-CARLA-3D: A Real and Synthetic Outdoor Point Cloud Dataset for Challenging Tasks in 3D Mapping
Jean-Emmanuel Deschaud, David Duque, Jean Pierre Richa +3
Paris-CARLA-3D is a dataset of several dense colored point clouds of outdoor environments built by a mobile LiDAR and camera system. The data are composed of two sets with syntheti…
A modular U-Net for automated segmentation of X-ray tomography images in composite materials
João P C Bertoldo, Etienne Decencière, David Ryckelynck +1
X-ray Computed Tomography (XCT) techniques have evolved to a point that high-resolution data can be acquired so fast that classic segmentation methods are prohibitively cumbersome,…
Scale Equivariant Neural Networks with Morphological Scale-Spaces
Mateus Sangalli, Samy Blusseau, Santiago Velasco-Forero +1
The translation equivariance of convolutions can make convolutional neural networks translation equivariant or invariant. Equivariance to other transformations (e.g. rotations, aff…
The structural properties of classical bulges and discs from z~2
Paola Dimauro, Marc Huertas-Company, Emanuele Daddi +19
We study the rest-frame optical mass-size relation of bulges and discs from z~2 to z~0 for a complete sample of massive galaxies in the CANDELS fields using 2 component Sérsic mode…
Deep Learning Identifies High-z Galaxies in a Central Blue Nugget Phase in a Characteristic Mass Range
M. Huertas-Company, J. R. Primack, A. Dekel +11
We use machine learning to identify in color images of high-redshift galaxies an astrophysical phenomenon predicted by cosmological simulations. This phenomenon, called the blue nu…
A catalog of polychromatic bulge-disk decompositions of ~ 17.600 galaxies in CANDELS
Paola Dimauro, Marc Huertas-Company, Emanuele Daddi +20
Understanding how bulges grow in galaxies is critical step towards unveiling the link between galaxy morphology and star-formation. To do so, it is necessary to decompose large sam…
Segmentation hiérarchique faiblement supervisée
Amin Fehri, Santiago Velasco-Forero, Fernand Meyer
Image segmentation is the process of partitioning an image into a set of meaningful regions according to some criteria. Hierarchical segmentation has emerged as a major trend in th…
The Strong Gravitational Lens Finding Challenge
R. Benton Metcalf, M. Meneghetti, Camille Avestruz +33
Large scale imaging surveys will increase the number of galaxy-scale strong lensing candidates by maybe three orders of magnitudes beyond the number known today. Finding these rare…
Deep learning for studies of galaxy morphology
D. Tuccillo, M. Huertas-Company, E. Decenciere +1
Establishing accurate morphological measurements of galaxies in a reasonable amount of time for future big-data surveys such as EUCLID, the Large Synoptic Survey Telescope or the W…
A New Spatio-Spectral Morphological Segmentation For Multi-Spectral Remote-Sensing Images
Guillaume Noyel, Jesus Angulo, Dominique Jeulin
A general framework of spatio-spectral segmentation for multi-spectral images is introduced in this paper. The method is based on classification-driven stochastic watershed (WS) by…
On distances, paths and connections for hyperspectral image segmentation
Guillaume Noyel, Jesus Angulo, Dominique Jeulin
The present paper introduces the and η connections in order to add regional information on -flat zones, which only take into account a local information. A top-down approach…
Fourier-based schemes for computing the mechanical response of composites with accurate local fields
François Willot
We modify the Green operator involved in Fourier-based computational schemes in elasticity, in 2D and 3D. The new operator is derived by expressing continuum mechanics in terms of…
Fourier-based schemes with modified Green operator for computing the electrical response of heterogeneous media with accurate local fields
François Willot, Bassam Abdallah, Yves-Patrick Pellegrini
A modified Green operator is proposed as an improvement of Fourier-based numerical schemes commonly used for computing the electrical or thermal response of heterogeneous media. Co…
Segmentation et Interprétation de Nuages de Points pour la Modélisation d'Environnements Urbains
Jorge Hernandez, Beatriz Marcotegui
Dans cet article, nous présentons une méthode pour la détection et la classification d'artefacts au niveau du sol, comme phase de filtrage préalable à la modélisation d'environneme…
Flooding edge or node weighted graphs
Fernand Meyer
Reconstruction closings have all properties of a physical flooding of a topographic surface. They are precious for simplifying gradient images or, filling unwanted catchment basins…
The watershed concept and its use in segmentation : a brief history
Fernand Meyer
The watershed is one of the most used tools in image segmentation. We present how its concept is born and developed over time. Its implementation as an algorithm or a hardwired dev…