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Nuclear recoil measurements with high-purity Germanium detectors are very promising to directly detect dark matter candidates. The main background sources in such experiments are natural radioactivity and microphonic noise. Digital pulse…
This research implements an advanced unsupervised clustering system for MNIST handwritten digits through two-phase deep autoencoder architecture. A deep neural autoencoder requires a training process during phase one to develop minimal yet…
This paper introduces an algorithm for the detection of change-points and the identification of the corresponding subsequences in transient multivariate time-series data (MTSD). The analysis of such data has become more and more important…
In this study we explore the possibility to use deep learning for the reconstruction of phase images from 4D scanning transmission electron microscopy (4D-STEM) data. The process can be divided into two main steps. First, the complex…
Porosity variations in tubular scaffolds are critical to reproducible, sophisticated applications of electrospun fibers in biomedicine. Established laser micrometry techniques produced ~14,000 datapoints enabling thickness and porosity…
Traditional weak-lensing mass reconstruction techniques suffer from various artifacts, including noise amplification and the mass-sheet degeneracy. In Hong et al. (2021), we demonstrated that many of these pitfalls of traditional mass…
Efficient and accurate algorithms are necessary to reconstruct particles in the highly granular detectors anticipated at the High-Luminosity Large Hadron Collider and the Future Circular Collider. We study scalable machine learning models…
Gas detectors are one of the pillars of the research in fundamental physics. Since many years, a new concept of detectors, the Micro Pattern Gas Detectors, allows to overcome many of the problems of other types of commonly used detectors,…
In the ATLAS Muon Spectrometer, Monitored Drift Tube (MDT) chambers and sMDT chambers with half of the tube diameter of the MDTs are used for precision muon track reconstruction. The sMDT chambers are designed for operation at high counting…
In this paper, we propose an original manner to employ a tangential cover algorithm - minDSS - in order to geometrically reconstruct noisy digital contours. To do so, we exploit the representation of graphical objects by maximal primitives…
We present here a new approach for using the intelligence aspects of artificial intelligence for knowledge discovery rather than device optimization in electromagnetic (EM) nanostructures. This approach uses training data obtained through…
A convolutional neural network (CNN) architecture is developed to improve the pulse shape discrimination (PSD) power of the gadolinium-loaded organic liquid scintillation detector to reduce the fast neutron background in the inverse beta…
Motivation: Structural heterogeneity in single-particle cryo-electron microscopy (cryo-EM) data represents a major challenge for high-resolution structure determination. Unsupervised classification may serve as the first step in the…
Statistical iterative reconstruction is expected to improve the image quality of megavoltage computed tomography (MVCT). However, one of the challenges of iterative reconstruction is its large computational cost. The purpose of this work is…
Improving resolution and sensitivity will widen possible medical applications of magnetic particle imaging. Pulsed excitation promises such benefits, at the cost of more complex hardware solutions and restrictions on drive field amplitude…
Superconducting lithographed resonators have a broad range of current and potential applications in the multiplexed readout of cryogenic detectors. Here, we focus on LC bandpass filters with resonances in the 1-5 MHz range used in the…
The widespread usage of high-definition screens on edge devices stimulates a strong demand for efficient image restoration algorithms. The way of caching deep learning models in a look-up table (LUT) is recently introduced to respond to…
Plasma tomography consists in reconstructing the 2D radiation profile in a poloidal cross-section of a fusion device, based on line-integrated measurements along several lines of sight. The reconstruction process is computationally…
In preparation for Higgs factories and energy-frontier facilities, future colliders are moving toward high-granularity calorimeters to improve reconstruction quality. However, the cost and construction complexity of such detectors is…
Cellular Electron Cryo-Tomography (CECT) is a powerful imaging technique for the 3D visualization of cellular structure and organization at submolecular resolution. It enables analyzing the native structures of macromolecular complexes and…