Related papers: Measuring the Gain of a Micro-Channel Plate/Phosph…
Nowadays, Microchannel Plate (MCP), as a kind of electron multipliers based on the secondary electron emission, is widely used in many high-sensitive experiments, such as neutrino detection, which require the noise to be as low as possible,…
Micro-channel plate (MCP) detectors, when used at pulsed-neutron-source instruments, offer the possibility of high spatial resolution and high contrast imaging with pixel-level spectroscopic information. Here we demonstrate the possibility…
Detection of low-intensity light relies on the conversion of photons to photoelectrons, which are then multiplied and detected as an electrical signal. To measure the actual intensity of the light, one must know the factor by which the…
We describe a high resolution imaging detector based on a single 80 mm micro-channel-plate (MCP) and a phosphor screen mounted on a UHV flange of only 100 mm inner diameter. It relies on standard components and we describe its performance…
One of the on-going issues with the use of microchannel plates (MCP) in the ionization profile monitors (IPM) at Fermilab is the significant decrease in gain over time. There are several possible issues that can cause this. Historically,…
Noise in image sensors led to the development of a whole range of denoising filters. A noisy image can become hard to recognize and often require several types of post-processing compensation circuits. This paper proposes an adaptive…
An advanced technique for a two-dimensional real time visualization of cluster beams in vacuum as well as of the overlap volume of cluster beams with particle accelerator beams is presented. The detection system consists of an array of…
Depth estimation from monocular images is a challenging problem in computer vision. In this paper, we tackle this problem using a novel network architecture using multi scale feature fusion. Our network uses two different blocks, first…
In this paper, we present our approach to systematically measure numerous performance parameters of MCP-PMTs. The experimental setups, the analyses and selected results are discussed. Although the techniques used may be different in other…
The build up of electron clouds inside a particle accelerator vacuum chamber can produce strong transverse and longitudinal beam instabilities which in turn can lead to high levels of beam loss often requiring the accelerator to be run…
Objective: Depth estimation is crucial for endoscopic navigation and manipulation, but obtaining ground-truth depth maps in real clinical scenarios, such as the colon, is challenging. This study aims to develop a robust framework that…
Traditional change detection methods based on convolutional neural networks (CNNs) face the challenges of speckle noise and deformation sensitivity for synthetic aperture radar images. To mitigate these issues, we proposed a Multiscale…
Modern momentum imaging techniques allow for the investigation of complex molecules in the gas phase by detection of several fragment ions in coincidence. For these studies, it is of great importance that the single-particle detection…
Traditional synthetic aperture radar image change detection methods based on convolutional neural networks (CNNs) face the challenges of speckle noise and deformation sensitivity. To mitigate these issues, we proposed a Multiscale Capsule…
Phosphorene, a two-dimensional (2D) monolayer of black phosphorus, has attracted considerable theoretical interest, although the experimental realization of monolayer, bilayer, and few-layer flakes has been a significant challenge. Here we…
In order to improve model accuracy, generalization, and class imbalance issues, this work offers a strong methodology for classifying endoscopic images. We suggest a hybrid feature extraction method that combines convolutional neural…
The topology and dynamics of the solar chromosphere are greatly affected by the presence of magnetic fields. The magnetic field can be inferred by analyzing polarimetric observations of spectral lines. Polarimetric signals induced by…
Event-based vision is an emerging research field involving processing data generated by Dynamic Vision Sensors (neuromorphic cameras). One of the latest proposals in this area are Graph Convolutional Networks (GCNs), which allow to process…
A non-destructive, real-time method for estimating the volume fraction of a dielectric mixture inside a resonant cavity is presented. A convolutional neural network (CNN)-based approach is used to estimate the fractional composition of…
Considering the use of Fully Connected (FC) layer limits the performance of Convolutional Neural Networks (CNNs), this paper develops a method to improve the coupling between the convolution layer and the FC layer by reducing the noise in…