Related papers: Low Activity Tritium Detection in CCDs Using Deep …
Thick, Charge Coupled Devices (CCDs) have recently been explored for applied physics, such as nuclear explosion monitoring, and dark matter detection purposes. When run in fully-depleted mode, these devices are sensitive detectors for…
This article details the potential for using Charge Coupled Devices (CCD) to detect low-energy neutrinos through their coherent scattering with nuclei. The detection of neutrinos through this standard model process has not been accessible…
A new detector is being developed at the National Superconducting Cyclotron Laboratory (NSCL) to measure low energy charged-particles from beta-delayed particle emission. These low energy particles are very important for nuclear…
Low noise CCDs fully-depleted up to 675 micrometers have been identified as a unique tool for Dark Matter searches and low energy neutrino physics. The charge collection efficiency (CCE) for these detectors is a critical parameter for the…
Charge-coupled devices (CCDs) are a leading technology in direct dark matter searches because of their eV-scale energy threshold and high spatial resolution. The sensitivity of future CCD experiments could be enhanced by distinguishing…
The purpose of this project is to investigate the use of charge couple devices (CCDs) to detect electrons directly. This can be done in transmission electron microscopy (TEM) for electrons over 100 KeV, but for space plasma instruments,…
Position-sensitive detectors for cold and ultra-cold neutrons (UCN) are in use in fundamental research. In particular, measuring the properties of the quantum states of bouncing neutrons requires micro-metric spatial resolution. To this…
Silicon Drift Detectors, widely employed in high-resolution and high-rate X-ray applications, are considered here with interest also for electron detection. The accurate measurement of the tritium beta decay is the core of the TRISTAN…
In the search for neutrinoless double-beta decay, the high-pressure gaseous Time Projection Chamber has a distinct advantage, because the ionization charge tracks produced by particle interactions are extended and the detector captures the…
The possibility of using CCD detectors in a low threshold direct detection dark matter search experiment is discussed. We present the main features of the DECam detectors that make them a good alternative for such an experiment, namely…
This paper proposes multiscale convolutional neural network (CNN)-based deep metric learning for bioacoustic classification, under low training data conditions. The proposed CNN is characterized by the utilization of four different filter…
Despite the indispensable role of X-ray computed tomography (CT) in diagnostic medicine field, the associated ionizing radiation is still a major concern considering that it may cause genetic and cancerous diseases. Decreasing the exposure…
Charge Coupled Devices (CCDs) have been successfully used in several high energy physics experiments over the past two decades. Their high spatial resolution and thin sensitive layers make them an excellent tool for studying short-lived…
The Dark Matter Time Projection Chamber (DMTPC) collaboration is developing a low pressure gas TPC for detecting Weakly Interacting Massive Particle (WIMP)-nucleon interactions. Optical readout with CCD cameras allows for the detection of…
Photon counting detectors (PCDs) bring valuable advantages to diagnostic computed tomography (CT), including lower noise and higher resolution than energy integrating detectors. However, there are still several nonideal factors preventing…
Convolutional Neural Networks (CNN) have been a good solution for understanding a vast image dataset. As the increased number of battery-equipped electric vehicles is flourishing globally, there has been much research on understanding which…
Effective and powerful methods for denoising real electrocardiogram (ECG) signals are important for wearable sensors and devices. Deep Learning (DL) models have been used extensively in image processing and other domains with great success…
Circulating Tumor Cells (CTCs) bear great promise as biomarkers in tumor prognosis. However, the process of identification and later enumeration of CTCs require manual labor, which is error-prone and time-consuming. The recent developments…
Purpose: Radiologists are tasked with visually scrutinizing large amounts of data produced by 3D volumetric imaging modalities. Small signals can go unnoticed during the 3d search because they are hard to detect in the visual periphery.…
Convolutional neural networks (CNNs) are widely used state-of-the-art computer vision tools that are becoming increasingly popular in high energy physics. In this paper, we attempt to understand the potential of CNNs for event…