Related papers: Multicomponent, multiwavelength benchmarks for sou…
High-quality astronomical images delivered by modern ground-based and space observatories demand adequate, reliable software for their analysis and accurate extraction of sources, filaments, and other structures, containing massive amounts…
Far-infrared imaging surveys of Galactic star-forming regions with Herschel have shown that a substantial part of the cold interstellar medium appears as a fascinating web of omnipresent filamentary structures. This highly anisotropic…
We present a multi-scale, multi-wavelength source extraction algorithm called getsources. Although it has been designed primarily for use in the far-infrared surveys of Galactic star-forming regions with Herschel, the method can be applied…
Context: Molecular clouds are the prime locations of star formation. These clouds contain filamentary structures and cores which are crucial in the formation of young stars. Aims: In this work, we aim to quantify the physical properties of…
We introduce ProFound, a source finding and image analysis package. ProFound provides methods to detect sources in noisy images, generate segmentation maps identifying the pixels belonging to each source, and measure statistics like flux,…
(Abridged) We describe a new method to extract spectra of stars from observations of crowded stellar fields with integral field spectroscopy (IFS). Our approach extends the well-established concept of crowded field photometry in images into…
We present the cross-identification and source photometry techniques used to process Herschel SPIRE imaging taken as part of the Herschel Multi-Tiered Extragalactic Survey (HerMES). Cross-identifications are performed in map-space so as to…
The Herschel Gould Belt survey mapped the nearby (d < 500 pc) star-forming regions to understand better how the prestellar phase influences the star formation process. Here we report a complete census of dense cores in a 15 deg2 area of the…
Context. Filaments are ubiquitous in the Galaxy, and they host star formation. Detecting them in a reliable way is therefore key towards our understanding of the star formation process. Aims. We explore whether supervised machine learning…
Large surveys using modern telescopes are producing images that are increasing exponentially in size and quality. Identifying objects in the generated images by visual recognition is time-consuming and labor-intensive, while classifying the…
A reliable extraction of filament data from microscopic images is of high interest in the analysis of acto-myosin structures as early morphological markers in mechanically guided differentiation of human mesenchymal stem cells and the…
Modern high-resolution images obtained with space observatories display extremely strong intensity variations across images on all spatial scales. Source extraction in such images with methods based on global thresholding may bring…
The initial and boundary conditions of the Galactic star formation in molecular clouds are not well understood. In an effort to shed new light on this long-standing problem, we measured properties of dense cores and filamentary structures…
We describe the method used to detect sources for the Herschel-ATLAS survey. The method is to filter the individual bands using a matched filter, based on the point-spread function (PSF) and confusion noise, and then form the inverse…
Analysing extended emission in photometric observations of star-forming regions requires maps free from compact foreground, embedded, and background sources, which can interfere with various techniques used to characterise the interstellar…
In the current era of radio astronomy, continuum surveys observe a multitude of objects with complex morphologies and sizes, and are not limited to observing point sources. Typical radio source extraction software generates catalogues by…
The GEneral description of Fission observables (GEF) model was developed to produce fission related nuclear data which are of crucial importance for basic and applied nuclear physics. The investigation of the performance of the GEF code is…
Cloud detection is an important preprocessing step for the precise application of optical satellite imagery. In this paper, we propose a deep learning based cloud detection method named multi-scale convolutional feature fusion (MSCFF) for…
We present the first results from the science demonstration phase for the Hi-GAL survey, the Herschel key-project that will map the inner Galactic Plane of the Milky Way in 5 bands. We outline our data reduction strategy and present some…
Aims. In astronomy, machine learning has been successful in various tasks such as source localisation, classification, anomaly detection, and segmentation. However, feature regression remains an area with room for improvement. We aim to…