The aim is to test whether texture descriptors can extract novel information about physical quantities of galaxies, which normally require spectroscopy to determine. The specific star formation rate (sSFR) is chosen as the quantity in question. Methods We use three sets of features: • Colours from five bandpass filters (no texture information). • Gradient orientation histograms computed at 8 scales, σ. • Shape index histograms computed at 8 scales, σ. Gradient orientation (GO) • GO, θ(x, y; σ), represents first order differential structure. • It is weighted by the scale normalized gradient magnitude, M(x, y; σ). • It is binned to histograms with 8 bins. θ(x, y; σ) = arcta
We present new spatially resolved surface photometry in the far-ultraviolet (FUV) and near-ultraviol...
The analysis of the light distribution of galaxy is a crucial step in studying their structural comp...
We devise improved photometric parameters for the morphological classification of galaxies using a b...
A texture descriptor based on the shape index and the accompanying curvedness measure is proposed, a...
A texture descriptor based on the shape index and the accompanying curvedness measure is proposed, a...
We give an approach to estimate galaxy morphology from digital images. In particular, our algorithm ...
Understanding the structure, formation and evolution of the Galactic Bulge requires the proper deter...
Using the HORIZON-AGN hydrodynamical simulation and self-organizing maps (SOMs), we show how to comp...
Abstract We investigate the radial color gradients of galactic disks using a sample of ∼ 20 000 face...
We investigate the radial color gradients of galactic disks using a sample of similar to 20 000 face...
This thesis aims to understand more about the developmental histories of galaxies and their internal...
International audienceWe explore how observations relate to the physical properties of the emitting ...
We present two new non-parametric methods for quantifying galaxy morphology: the relative distributi...
We present a new approach based on Supervised Machine Learning algorithms to infer key physical prop...
International audienceBased on the recent advancements in the numerical simulations of galaxy format...
We present new spatially resolved surface photometry in the far-ultraviolet (FUV) and near-ultraviol...
The analysis of the light distribution of galaxy is a crucial step in studying their structural comp...
We devise improved photometric parameters for the morphological classification of galaxies using a b...
A texture descriptor based on the shape index and the accompanying curvedness measure is proposed, a...
A texture descriptor based on the shape index and the accompanying curvedness measure is proposed, a...
We give an approach to estimate galaxy morphology from digital images. In particular, our algorithm ...
Understanding the structure, formation and evolution of the Galactic Bulge requires the proper deter...
Using the HORIZON-AGN hydrodynamical simulation and self-organizing maps (SOMs), we show how to comp...
Abstract We investigate the radial color gradients of galactic disks using a sample of ∼ 20 000 face...
We investigate the radial color gradients of galactic disks using a sample of similar to 20 000 face...
This thesis aims to understand more about the developmental histories of galaxies and their internal...
International audienceWe explore how observations relate to the physical properties of the emitting ...
We present two new non-parametric methods for quantifying galaxy morphology: the relative distributi...
We present a new approach based on Supervised Machine Learning algorithms to infer key physical prop...
International audienceBased on the recent advancements in the numerical simulations of galaxy format...
We present new spatially resolved surface photometry in the far-ultraviolet (FUV) and near-ultraviol...
The analysis of the light distribution of galaxy is a crucial step in studying their structural comp...
We devise improved photometric parameters for the morphological classification of galaxies using a b...