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We present the pulsar_spectra software repository, an open-source pulsar flux density catalogue and automated spectral fitting software that finds the best spectral model and produces publication-quality plots. The Python-based software…
Mahotas is a computer vision library for Python. It contains traditional image processing functionality such as filtering and morphological operations as well as more modern computer vision functions for feature computation, including…
In this work, we present a Web-based annotation tool `Relation Triplets Extractor' \footnote{https://abera87.github.io/annotate/} (RTE) for annotating relation triplets from the text. Relation extraction is an important task for extracting…
In this paper we describe a new method for detecting and counting a repeating object in an image. While the method relies on a fairly sophisticated deformable part model, unlike existing techniques it estimates the model parameters in an…
Weakly-supervised object localization methods tend to fail for object classes that consistently co-occur with the same background elements, e.g. trains on tracks. We propose a method to overcome these failures by adding a very small amount…
In the last decade, over a million stars were monitored to detect transiting planets. Manual interpretation of potential exoplanet candidates is labor intensive and subject to human error, the results of which are difficult to quantify.…
We demonstrate that gravitational lensing can be used to discover and study planets in the habitable zones of nearby dwarf stars. If appropriate software is developed, a new generation of monitoring programs will automatically conduct a…
We present a Python-based framework for the complete operation of a robotic telescope observatory. It provides out-of-the-box support for many popular camera types while other hardware like telescopes, domes, and weather stations can easily…
Aiming to address the fast multi-object tracking for dense small object in the cluster background, we review track orientated multi-hypothesis tracking(TOMHT) with consideration of batch optimization. Employing autocorrelation based motion…
Event-based eye tracking is a promising solution for efficient and low-power eye tracking in smart eyewear technologies. However, the novelty of event-based sensors has resulted in a limited number of available datasets, particularly those…
Microlensing light curves are now being monitored with the precision required to detect small perturbations due to planetary companions of the primary lens. Microlensing is complementary to other planetary search techniques in its potential…
Occultations, the covering up of one celestial body by another celestial body, have been used in astronomy for millennia to learn about the sun and moon. Since 2018, VERITAS has implemented a program to detect predicted asteroid…
Correlation clustering is a technique for aggregating data based on qualitative information about which pairs of objects are labeled 'similar' or 'dissimilar.' Because the optimization problem is NP-hard, much of the previous literature…
We present Pandora, a new software to model, detect, and characterize transits of extrasolar planets with moons in stellar photometric time series. Pandora uses an analytical description of the transit light curve for both the planet and…
PlanetPack, initially released in 2013, is a command-line software aimed to facilitate exoplanets detection, characterization, and basic dynamical $N$-body simulations. This paper presents the third major release of PlanetPack that…
All the fields of the extended space mission Kepler/K2 are located within the ecliptic. Many solar system objects thus cross the K2 stellar masks on a regular basis. We aim at providing to the entire community a simple tool to search and…
ArchNEMESIS is an open-source Python package developed for the analysis of remote sensing spectroscopic observations of planetary atmospheres. It is based on the widely used NEMESIS radiative transfer and retrieval tool, which has been…
Soft labels in image classification are vector representations of an image's true classification. In this paper, we investigate soft labels in the context of satellite object detection. We propose using detections as the basis for a new…
The tracking-by-detection paradigm today has become the dominant method for multi-object tracking and works by detecting objects in each frame and then performing data association across frames. However, its sequential frame-wise matching…
Visual multi-object tracking has the potential to accelerate many forms of quantitative analyses, especially in research communities investigating the motion, behavior, or social interactions within groups of animals. Despite its potential…