Related papers: Development of Convolutional Neural Networks for a…
A new method for directional fast neutron detection is proposed based on a neutron time projection chamber (TPC) and position-sensitive plastic scintillation detectors. The detection system can efficiently locate the approximate location of…
The Liquid Xenon Gamma-Ray Imaging Telescope (LXeGRIT) is a balloon born experiment sensitive to \g -rays in the energy band of 0.2-20 MeV. The main detector is a time projection chamber filled with high purity liquid xenon (LXeTPC), in…
The non-linear Compton scattering rate in a rotating electric field is explicitly calculated for the first time. For this purpose, a novel solution to the Klein-Gordon equation in the presence of a rotating electric field is applied. An…
We describe a feasible implementation of a novel X-ray detector for highly energetic x-ray photons with a large solid angle coverage, optimal for the detection of Compton x-ray scattered photons. The device consists of a 20~cm-thick…
Track reconstruction algorithms are critical for polarization measurements. In addition to traditional moment-based track reconstruction approaches, convolutional neural networks (CNN) are a promising alternative. However, hexagonal grid…
High-energy gamma-ray spectroscopy is crucial for studying and advancing the application of high-energy photons in areas like strong-field physics, high-energy-density science, and laboratory astrophysics. However, high-energy gamma-ray…
Estimation of the optical properties of scattering media such as tissue is important in diagnostics as well as in the development of techniques to image deeper. As light penetrates the sample scattering events occur that alter the…
Exoplanet observations are currently analysed with Bayesian retrieval techniques. Due to the computational load of the models used, a compromise is needed between model complexity and computing time. Analysis of data from future facilities,…
Terrain relative navigation can improve the precision of a spacecraft's position estimate by detecting global features that act as supplementary measurements to correct for drift in the inertial navigation system. This paper presents a…
GRETA, the Gamma-Ray Energy Tracking Array, is an array of highly-segmented HPGe detectors designed to track {\gamma}-rays emitted in beam-physics experiments. Its high detection efficiency and state-of-the-art position resolution make it…
Low-energy electron recoils are of interest in several planned and proposed future nuclear and particle physics experiments. The topology and directions of such recoils provide important particle identification and kinematical constraints,…
Convolutional Neural Networks (CNNs) are a class of artificial neural networks whose computational blocks use convolution, together with other linear and non-linear operations, to perform classification or regression. This paper explores…
In this work we describe a Convolutional Neural Network (CNN) to accurately predict the scene illumination. Taking image patches as input, the CNN works in the spatial domain without using hand-crafted features that are employed by most…
A cluster imaging technique for Transmission Electron Microscopy with a direct detection CMOS pixel sensor is presented. Charge centre-of-gravity reconstruction for individual electron clusters improves the spatial resolution and thus the…
We have combined transmission speckle photography and machine learning for direct classification and recognition of milk fat content classes. Our aim was hinged on the fact that parameters of scattering particles (and the dispersion medium)…
Summary: Errors in gradient trajectories introduce significant artifacts and distortions in magnetic resonance images, particularly in non-Cartesian imaging sequences, where imperfect gradient waveforms can greatly reduce image quality.…
Head pose estimation and tracking is useful in variety of medical applications. With the advent of RGBD cameras like Kinect, it has become feasible to do markerless tracking by estimating the head pose directly from the point clouds. One…
Compton scattering of a laser beam with a relativistic electron beam has been used to generate intense, highly polarized and nearly monoenergetic x-ray or gamma-ray beams at many facilities. The ability to predict the spatial, spectral and…
Imaging through scattering is an important, yet challenging problem. Tremendous progress has been made by exploiting the deterministic input-output "transmission matrix" for a fixed medium. However, this "one-to-one" mapping is highly…
Multi-target tracking (MTT) is a classical signal processing task, where the goal is to estimate the states of an unknown number of moving targets from noisy sensor measurements. In this paper, we revisit MTT from a deep learning…