Related papers: Denoising radio pulses from air showers using mach…
Real-world image noise removal is a long-standing yet very challenging task in computer vision. The success of deep neural network in denoising stimulates the research of noise generation, aiming at synthesizing more clean-noisy image pairs…
Over the last years, radio detection has matured to become a competitive method for the detection of air showers. Arrays of thousands of antennas are now envisioned for the detection of cosmic rays of ultra high energy or neutrinos of…
Over the last decades, radio detection of air showers has been established as a detection technique for ultra-high-energy cosmic-rays impinging on the Earth's atmosphere with energies far beyond LHC energies. Today's second-generation of…
Deep neural networks are a powerful technique that have found ample applications in several branches of Physics. In this work, we apply machine learning algorithms to a specific problem of Cosmic Ray Physics: the estimation of the muon…
In spectroscopic experiments, data acquisition in multi-dimensional phase space may require long acquisition time, owing to the large phase space volume to be covered. In such case, the limited time available for data acquisition can be a…
Radio antennas have become a standard tool for the detection of cosmic-ray air showers in the energy range above $10^{16}\,$eV. The radio signal of these air showers is generated mostly due to the deflection of electrons and positrons in…
For centuries, scientists have observed nature to understand the laws that govern the physical world. The traditional process of turning observations into physical understanding is slow. Imperfect models are constructed and tested to…
When capturing and storing images, devices inevitably introduce noise. Reducing this noise is a critical task called image denoising. Deep learning has become the de facto method for image denoising, especially with the emergence of…
Recent studies on learning-based image denoising have achieved promising performance on various noise reduction tasks. Most of these deep denoisers are trained either under the supervision of clean references, or unsupervised on synthetic…
As of early 2025, the GRAND Collaboration operates three prototype arrays: GRANDProto300 in China, GRAND@Nan\c{c}ay in France, and GRAND@Auger in Argentina. The GRAND@Auger prototype was established through an agreement between the GRAND…
This review provides an introduction to the radio emission by particle cascades, an overview on the various experiments, and explains methods for the radio measurement of air-shower properties. Furthermore, potential applications of the…
GRANDProto300 is the planned 300-antenna pathfinder array of the Giant Radio Array for Neutrino Detection (GRAND), of which the first 100 detection units have been already produced. Its main goal is to demonstrate the viability of the…
Next-generation particle accelerators demand advanced beam-diagnostic capabilities to ensure high performance, operational reliability, and sustainable machine operation. Increasing beam intensities and stored energies make the precise…
In many scientific applications, measured time series are corrupted by noise or distortions. Traditional denoising techniques often fail to recover the signal of interest, particularly when the signal-to-noise ratio is low or when certain…
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,…
We propose a machine-learning-based technique to determine the number density of radio sources as a function of their flux density, for use in next-generation radio surveys. The method uses a convolutional neural network trained on…
De-noising plays a crucial role in the post-processing of spectra. Machine learning-based methods show good performance in extracting intrinsic information from noisy data, but often require a high-quality training set that is typically…
Acoem develops gunshot detection systems, consisting of a microphone array and software that detects and locates shooters on the battlefield. The performance of such systems is obviously affected by the acoustic environment in which they…
The detection of extensive air showers (EAS) through their radio signal is becoming one of the most promising techniques for the study of Neutrinos and Cosmic rays at the highest energies. For the design, optimization and characterization…
Radar images of humans and other concealed objects are considerably distorted by attenuation, refraction and multipath clutter in indoor through-wall environments. While several methods have been proposed for removing target independent…