Related papers: WARP: The Data Reduction Pipeline for the WINERED …
We report precipitable water vapor (PWV) measurements made at Las Campanas Observatory using optical spectra of H2O lines obtained with the Magellan echelle spectrograph, and calculated using a robust technique that is accurate to 5-10%.…
Downsampling images and labels, often necessitated by limited resources or to expedite network training, leads to the loss of small objects and thin boundaries. This undermines the segmentation network's capacity to interpret images…
In this contribution, we define (and test) a pipeline to perform virtual painting recolouring using raw data of X-Ray Fluorescence (XRF) analysis on pictorial artworks. To circumvent the small dataset size, we generate a synthetic dataset,…
I present spherical (https://github.com/m-samland/spherical), a software package and database designed for the ESO VLT/SPHERE high-contrast imager. SPHERE has produced the world's largest archive of direct imaging observations of exoplanets…
Sparse regularization is fundamental in signal processing and feature extraction but often relies on non-differentiable penalties, conflicting with gradient-based optimizers. We propose WEEP (Weakly-convex Envelope of Piecewise Penalty), a…
Accurate estimation of wheat spike volume is important for yield component analysis and stress resilience assessment, yet field-based measurement remains challenging. Active 3D sensing methods such as Light Detection and Ranging (LiDAR) or…
The deep learning (DL)-based methods of low-level tasks have many advantages over the traditional camera in terms of hardware prospects, error accumulation and imaging effects. Recently, the application of deep learning to replace the image…
We describe the design and construction of a formatted fiber field-unit, SparsePak, and characterize its optical and astrometric performance. This array is optimized for spectroscopy of low-surface brightness, extended sources in the…
The Spectral Energy Distribution (SED) mode of the Multiband Imaging Photometer for Spitzer (MIPS) Space Telescope provides low-spectral resolution (R ~ 15-25) spectroscopy in the far infrared using the MIPS 70 um detector. A reflective…
Virtually imaged phased array (VIPA) spectrometers provide high resolution and fast acquisition in a compact design, but their performance as dispersive instruments is sensitive to fabrication tolerances, component dimensions, and…
IOP4 is a pipeline to perform photometry and polarimetry analysis of optical data from Calar Alto (CAHA) and Sierra Nevada (OSN) observatories. IOP4 implements Object Relational Mapping (ORM) to seamlessly integrate all information about…
The Bluebild algorithm is a new technique for image synthesis in radio astronomy which decomposes the sky into distinct energy levels using functional principal component analysis. These levels can be linearly combined to construct a…
In this paper, we propose a perceptually-guided visualization sharpening technique. We analyze the spectral behavior of an established comprehensive perceptual model to arrive at our approximated model based on an adapted weighting of the…
Observations in the near-infrared using large ground-based telescopes are adversely impacted by bright atmospheric emission lines, particularly the OH Meinel bands. These lines can saturate a moderate-resolution spectrograph on the order of…
Building on prior FAST targeted and blind SETI campaigns toward 33 exoplanet systems, we introduce a wavelet-integrated search pipeline for narrowband technosignature candidates in radio dynamic spectra. At its core, the pipeline uses a…
The Extremely Large Telescopes (ELTs), thanks to their large apertures and cutting-edge Multi-Conjugate Adaptive Optics (MCAO) systems, promise to deliver sharper and deeper data even than the JWST. SHARP is a concept study for a near-IR…
We propose a new unsupervised anomaly detection method based on the sliced-Wasserstein distance for training data selection in machine learning approaches. Our filtering technique is interesting for decision-making pipelines deploying…
Dataset distillation compresses large datasets into smaller synthetic coresets which retain performance with the aim of reducing the storage and computational burden of processing the entire dataset. Today's best-performing algorithm,…
Comparison of echelle spectra to synthetic models has become a computational statistics challenge, with over ten thousand individual spectral lines affecting a typical cool star echelle spectrum. Telluric artifacts, imperfect line lists,…
Compressive sampling has great potential for making wideband spectrum sensing possible at sub-Nyquist sampling rates. As a result, there have recently been research efforts that leverage compressive sampling to enable efficient wideband…