International audienceWe extend a recently developed galaxy morphology classification method, Quantitative Multiwavelength Morphology (QMM), to connect galaxy morphologies to their underlying physical properties. The traditional classification of galaxies approaches the problem separately through either morphological classification or, in more recent times, analysis of physical properties. A combined approach has significant potential in producing a consistent and accurate classification scheme as well as shedding light on the origin and evolution of galaxy morphology. Here, we present an analysis of a volume-limited sample of 31 703 galaxies from the fourth data release of the Sloan Digital Sky Survey. We use an image analysis method calle...
Context. Machine learning methods are effective tools in astronomical tasks for classifying objects ...
Galaxy morphology is a fundamental quantity, which is essential not only for the full spectrum of ga...
In this paper, we show that the determination of the morphological type could be difficult when we o...
International audienceWe extend a recently developed galaxy morphology classification method, Quanti...
We extend a recently developed galaxy morphology classification method, Quantitative Multiwavelength...
We give an approach to estimate galaxy morphology from digital images. In particular, our algorithm ...
We devise improved photometric parameters for the morphological classification of galaxies using a b...
The goal of galaxy classification is to understand the physical basis for the wide range in shapes a...
Abstract: We present an application of Mathematical Morphology (MM) for the classification of astro-...
We present two new non-parametric methods for quantifying galaxy morphology: the relative distributi...
We present a quantitative method to classify galaxies, based on multi-wavelength data and constructe...
We present the data release for Galaxy Zoo 2 (GZ2), a citizen science project with more than 16 mill...
Studying the evolution of the morphological distribution of galaxies in different environments can p...
We present the data release for Galaxy Zoo 2 (GZ2), a citizen science project with more than 16 mill...
We present the morphological catalogue of galaxies in nearby clusters of the WIde-field Nearby Galax...
Context. Machine learning methods are effective tools in astronomical tasks for classifying objects ...
Galaxy morphology is a fundamental quantity, which is essential not only for the full spectrum of ga...
In this paper, we show that the determination of the morphological type could be difficult when we o...
International audienceWe extend a recently developed galaxy morphology classification method, Quanti...
We extend a recently developed galaxy morphology classification method, Quantitative Multiwavelength...
We give an approach to estimate galaxy morphology from digital images. In particular, our algorithm ...
We devise improved photometric parameters for the morphological classification of galaxies using a b...
The goal of galaxy classification is to understand the physical basis for the wide range in shapes a...
Abstract: We present an application of Mathematical Morphology (MM) for the classification of astro-...
We present two new non-parametric methods for quantifying galaxy morphology: the relative distributi...
We present a quantitative method to classify galaxies, based on multi-wavelength data and constructe...
We present the data release for Galaxy Zoo 2 (GZ2), a citizen science project with more than 16 mill...
Studying the evolution of the morphological distribution of galaxies in different environments can p...
We present the data release for Galaxy Zoo 2 (GZ2), a citizen science project with more than 16 mill...
We present the morphological catalogue of galaxies in nearby clusters of the WIde-field Nearby Galax...
Context. Machine learning methods are effective tools in astronomical tasks for classifying objects ...
Galaxy morphology is a fundamental quantity, which is essential not only for the full spectrum of ga...
In this paper, we show that the determination of the morphological type could be difficult when we o...