Related papers: RVSNUpy: A Python Package for Spectroscopic Redshi…
Predictive constitutive equations that connect easy-to-measure transport properties (e.g., viscosity and conductivity) with system performance variables (e.g., power consumption and efficiency) are needed to design advanced thermal and…
Developmental dysplasia of the hip (DDH) poses significant diagnostic challenges, hindering timely intervention. Current screening methodologies lack standardization, and AI-driven studies suffer from reproducibility issues due to limited…
We use a dense redshift survey in the foreground of the Subaru GTO2deg^2 weak lensing field (centered at $\alpha_{2000}$ = 16$^h04^m44^s$;$\delta_{2000}$ =43^\circ11^{\prime}24^{\prime\prime}$) to assess the completeness and comment on the…
Gammapy is a Python package for high-level gamma-ray data analysis built on Numpy, Scipy and Astropy. It enables us to analyze gamma-ray data and to create sky images, spectra and lightcurves, from event lists and instrument response…
As a consequence of galaxy clustering, close galaxies observed on the plane of the sky should be spatially correlated with a probability that is inversely proportional to their angular separation. In principle, this information can be used…
Three-dimensional rigid-body transforms, i.e. rotations and translations, are central to modern differentiable machine learning pipelines in robotics, vision, and simulation. However, numerically robust and mathematically correct…
The ignition delay of a fuel/air mixture is an important quantity in designing combustion devices, and these data are also used to validate chemical kinetic models for combustion. One of the typical experimental devices used to measure the…
We present the COSMOS Spectroscopic Redshift Compilation encompassing ~ 20 years of spectroscopic redshifts within a 10 deg$^2$ area centered on the 2 deg$^2$ COSMOS legacy field. This compilation contains 487,666 redshifts of 266,284…
Remote sensing change detection aims to compare two or more images recorded for the same area but taken at different time stamps to quantitatively and qualitatively assess changes in geographical entities and environmental factors.…
X-ray Photoelectron Spectroscopy (XPS) is a crucial technique for material surface analysis, yet interpreting its spectra is often challenging for both human analysts and automated methods due to the prevalence of variable spectral shifts…
This paper presents the results of the redshift survey of 138 candidate compact groups from the DPOSS II catalog (Iovino et al., 2003; de Carvalho et al. 2005), which extends the available redshift range of spectroscopically confirmed…
We present a description of the observations and data reduction procedures for an extensive spectroscopic and multi-band photometric study of nine high redshift, optically-selected cluster candidates. The primary goal of the survey is to…
We present a new cluster-finding algorithm based on a combination of the Voronoi Tessellation and Friends-Of-Friends methods. The algorithm utilises probability distribution functions derived from a photometric redshift analysis. We test…
We present a photometric redshift (photo-$z$) estimation technique for galaxies in the P\lowercase{an}-STARRS1 (PS1) $3\pi $ survey. Specifically, we train and test a regression and a classification Random-Forest (RF) models using…
We introduce our Radial Velocity Survey for Planets around Young stars (RVSPY), characterise our target stars, and search for substellar companions at orbital separations smaller than a few au from the host star. We use the FEROS…
With the advent of very large volume, wide-angle photometric redshift surveys like e.g. Pan-STARRS, DES, or PAU, which aim at using the spatial distribution of galaxies as a means to constrain the equation of state parameter of dark energy,…
Remote sensing image scene classification plays an important role in a wide range of applications and hence has been receiving remarkable attention. During the past years, significant efforts have been made to develop various datasets or…
Handling big data has largely been a major bottleneck in traditional statistical models. Consequently, when accurate point prediction is the primary target, machine learning models are often preferred over their statistical counterparts for…
We calculate photometric redshifts from the Sloan Digital Sky Survey Data Release 2 Galaxy Sample using artificial neural networks (ANNs). Different input patterns based on various parameters (e.g. magnitude, color index, flux information)…
We present a novel method for scene change detection that leverages the robust feature extraction capabilities of a visual foundational model, DINOv2, and integrates full-image cross-attention to address key challenges such as varying…