Related papers: Offline Signal Identification with GRANDProto300
We investigate the possibility of searching for ultra high energy neutrinos in cosmic rays using acoustic techniques in ocean water. The type of information provided by the acoustic detection is complementary to that of other techniques,…
Despite notable advancements in the field of computer vision, the precise detection of tiny objects continues to pose a significant challenge, largely owing to the minuscule pixel representation allocated to these objects in imagery data.…
We present a new method, based on fractal analysis, to characterize the output of a physical detector that is in the form of a set of real-valued, discrete physical measurements. We apply the method to gravitational-wave data from the…
The impending era of wide-field radio surveys has the potential to revolutionize our understanding of astrophysical transients. Here we evaluate the prospects of a wide range of planned and hypothetical radio surveys using the properties…
Deep learning identification models have shown promise for identifying gas plumes in Longwave IR hyperspectral images of urban scenes, particularly when a large library of gases are being considered. Because many gases have similar spectral…
Far-infrared detectors for future cooled space telescopes require ultra-sensitive detectors with optical noise equivalent powers of order 0.2 aW/\sqrt Hz. This performance has already been demonstrated in arrays of transition edge sensors.…
We apply classical machine vision and machine deep learning methods to prototype signal classifiers for the search for extraterrestrial intelligence. Our novel approach uses two-dimensional spectrograms of measured and simulated radio…
Convolutional Neural Networks (CNNs) have demonstrated potential for the real-time analysis of data from gravitational-wave detector networks for the specific case of signals from coalescing compact-object binaries such as black-hole…
Radio frequency fingerprint identification (RFFI) can classify wireless devices by analyzing the signal distortions caused by the intrinsic hardware impairments. State-of-the-art neural networks have been adopted for RFFI. However, many…
Exploration of the time-domain radio sky has huge potential for advancing our knowledge of the dynamic universe. Past surveys have discovered large numbers of pulsars, rotating radio transients and other transient radio phenomena; however,…
We present an in-situ antenna characterization method and results for a "low-frequency" radio astronomy engineering prototype array, characterized over the 75-300 MHz frequency range. The presence of multiple cosmic radio sources,…
Using advanced machine learning techniques, we developed a method for reconstructing precisely the arrival direction and energy of ultra-high-energy cosmic rays from the voltage traces they induced on ground-based radio detector arrays. In…
Grand Unification of the strong, weak and electromagnetic interactions into a single unified gauge group is an extremely appealing idea which has been vigorously pursued theoretically and experimentally for many years. The detection of…
Ubiquitously deployed Internet of Things (IoT)- based automatic vehicle classification systems will catalyze data-driven traffic flow optimization in future smart cities and will transform the road infrastructure itself into a dynamically…
The deployment of several large scale arrays is envisioned to study astroparticles at ultra-high energies. In order to circumvent the heavy computational costs of exploring and optimizing their layouts, we have developed a pruning method.…
We present results from applying the SNAD anomaly detection pipeline to the third public data release of the Zwicky Transient Facility (ZTF DR3). The pipeline is composed of 3 stages: feature extraction, search of outliers with machine…
The next generation of the IceCube Neutrino Observatory, IceCube-Gen2, will constitute a much larger detector, increasing the rate of high-energy neutrinos. IceCube-Gen2 will address the long-standing questions about astrophysical…
The rapidly growing volume of drone air traffic demands improved radar surveillance systems and increased detection reliability in challenging conditions. The scattering cross-section, which characterizes a target's radar visibility, is a…
The Search for Extra-terrestrial Intelligence (SETI) aims to find technological signals of extra-solar origin. Radio frequency SETI is characterized by large unlabeled datasets and complex interference environment. The infinite…
Technical and environmental noise in ground-based laser interferometers designed for gravitational-wave observations like Advanced LIGO, Advanced Virgo and KAGRA, can manifest as narrow (<1Hz) or broadband ($10'$s or even $100'$s of Hz)…