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We propose SAM-Road, an adaptation of the Segment Anything Model (SAM) for extracting large-scale, vectorized road network graphs from satellite imagery. To predict graph geometry, we formulate it as a dense semantic segmentation task,…
We explored the impact of the synergy between the Euclid near-infrared photometric surveys and the SKA radio continuum surveys on the studies of the cosmic star formation. The Euclid satellite is expected to perform a Wide and Deep…
With the launch and application of next-generation ground- and space-based telescopes, astronomy has entered the era of big data, necessitating more efficient and robust data analysis methods. Most traditional parameter estimation methods…
Training segmentation models for medical images continues to be challenging due to the limited availability of data annotations. Segment Anything Model (SAM) is a foundation model that is intended to segment user-defined objects of interest…
We present mock JWST observations for more than 250,000 different galaxies from the Astrid simulation with $3 \leq z \leq 6$. The mock observations are made using the BPASS stellar SED model, and a simple dust model. They are then viewed…
Automated nodule segmentation is essential for computer-assisted diagnosis in ultrasound images. Nevertheless, most existing methods depend on precise pixel-level annotations by medical professionals, a process that is both costly and…
The Segment Anything Model (SAM) has achieved remarkable successes in the realm of natural image segmentation, but its deployment in the medical imaging sphere has encountered challenges. Specifically, the model struggles with medical…
This paper seeks to test if the large-scale galaxy distribution can be characterized as a fractal system. Tools appropriate for describing galaxy fractal structures with a single fractal dimension $D$ in relativistic settings are developed…
The Segment Anything Model (SAM) made an eye-catching debut recently and inspired many researchers to explore its potential and limitation in terms of zero-shot generalization capability. As the first promptable foundation model for…
Abstract abridged. The eROSITA X-ray telescope aboard the SRG orbital observatory, in the course of its all-sky survey, is expected to detect about three million active galactic nuclei (AGN) and hundred thousand clusters and groups of…
We develop a fully non-invasive use of machine learning in order to enable open research on Euclid-sized data sets. Our algorithm leaves complete control over theory and data analysis, unlike many black-box like uses of machine learning.…
Red clump stars (RCs) are useful tracers of distances, extinction, chemical abundances, and Galactic structures and kinematics. Accurate estimation of the RC parameters -- absolute magnitude and intrinsic color -- is the basis for obtaining…
Leveraging the Segment Anything Model (SAM) for medical image segmentation remains challenging due to its limited adaptability across diverse medical domains. Although fine-tuned variants, such as MedSAM, improve performance in scenarios…
Kinematical parameterisations of disc galaxies, employing emission line observations, are indispensable tools for studying the formation and evolution of galaxies. Future large-scale HI surveys will resolve the discs of many thousands of…
Segment anything model (SAM), a foundation model with superior versatility and generalization across diverse segmentation tasks, has attracted widespread attention in medical imaging. However, it has been proved that SAM would encounter…
The Euclid mission $-$ with its spectroscopic galaxy survey covering a sky area over $15\,000 \ \mathrm{deg}^2$ in the redshift range $0.9<z<1.8\ -$ will provide a sample of tens of thousands of cosmic voids. This paper explores for the…
Accurately identifying and representing object edges is a challenging task in computer vision and image processing. The Segment Anything Model (SAM) has significantly influenced the field of image segmentation, but suffers from high memory…
The spatial variation of the colour of a galaxy may introduce a bias in the measurement of its shape if the PSF profile depends on wavelength. We study how this bias depends on the properties of the PSF and the galaxies themselves. The bias…
In this report we present experimental results using \emph{Haussdorf-Besicovich} fractal dimension for performing morphological galaxy classification. The fractal dimension is a topological, structural and spatial property that give us…
We present NIR surface photometry of 11 edge-on galaxies obtained in the course of a long term project aimed at analysing the occurrence and type of the truncation of the outer disks. Observations were carried out at the 1.5 m CST (Carlos…