Related papers: Towards Real-time Classification of Astronomical T…
Previous deep learning-based event denoising methods mostly suffer from poor interpretability and difficulty in real-time processing due to their complex architecture designs. In this paper, we propose window-based event denoising, which…
The exponential growth of astronomical data from large-scale surveys has created both opportunities and challenges for the astrophysics community. This paper explores the possibilities offered by transfer learning techniques in addressing…
Many photometric time-domain surveys are driven by specific goals, such as searches for supernovae or transiting exoplanets, which set the cadence with which fields are re-imaged. In the case of the Palomar Transient Factory (PTF), several…
The brightest events in a time series of cosmological transients obey an observation time dependence which is often overlooked. This dependence can be exploited to probe the global properties of electromagnetic and gravitational wave…
The data taken by the advanced LIGO and Virgo gravitational-wave detectors contains short duration noise transients that limit the significance of astrophysical detections and reduce the duty cycle of the instruments. As the advanced…
The Gamma-ray Burst Monitor (GBM) on board Fermi Gamma-ray Space Telescope has produced the largest database of all-sky observations in gamma rays with its continuous data with high time and energy resolutions. These data contain a wealth…
Most existing star-galaxy classifiers use the reduced summary information from catalogs, requiring careful feature extraction and selection. The latest advances in machine learning that use deep convolutional neural networks allow a machine…
For transient sources with timescales of 1-100 seconds, standardized imaging for all observations at each time step become impossible as large modern interferometers produce significantly large data volumes in this observation time frame.…
Cross-match spatially clusters and organizes several astronomical point-source measurements from one or more surveys. Ideally, each object would be found in each survey. Unfortunately, the observation conditions and the objects themselves…
How to analyse Terabytes of photometric data, and extract knowledge on variable stars? How to detect variable phenomena? How to combine different photometric bands? Which algorithm to search for periods? How to characterize and classify the…
Aerial surveillance demands rapid and precise detection of moving objects in dynamic environments. Event cameras, which draw inspiration from biological vision systems, present a promising alternative to frame-based sensors due to their…
The increasing data volume of high-energy space monitors necessitates real-time, automated transient classification for multi-messenger follow-up. Conventional methods rely on empirical features like hardness ratios and reliable…
The Australian Square Kilometre Array Pathfinder (ASKAP) will give us an unprecedented opportunity to investigate the transient sky at radio wavelengths. In this paper we present VAST, an ASKAP survey for Variables and Slow Transients. VAST…
The detection and tracking of celestial surface terrain features are crucial for autonomous spaceflight applications, including Terrain Relative Navigation (TRN), Entry, Descent, and Landing (EDL), hazard analysis, and scientific data…
The current data acquisition rate of astronomical transient surveys and the promise for significantly higher rates during in the next decade necessitate the development of novel approaches to analyze astronomical data sets and promptly…
We analyze the prospects of employing a distributed global network of precision measurement devices as a dark matter and exotic physics observatory. In particular, we consider the atomic clocks of the Global Positioning System (GPS),…
Anomalies in the domain of autonomous driving are a major hindrance to the large-scale deployment of autonomous vehicles. In this work, we focus on high-resolution camera data from urban scenes that include anomalies of various types and…
Tackling the most pressing problems for humanity, such as the climate crisis and the threat of global pandemics, requires accelerating the pace of scientific discovery. While science has traditionally relied on trial and error and even…
Wide field small aperture telescopes are widely used for optical transient observations. Detection and classification of astronomical targets in observed images are the most important and basic step. In this paper, we propose an…
Real-time analysis and classification of observational data collected within synoptic sky surveys is a huge challenge due to constant growth of data volumes. Machine learning techniques are often applied in order to perform this task…