Related papers: DECal, a Python tool for the efficiency calculatio…
Surface defect detection is an extremely crucial step to ensure the quality of industrial products. Nowadays, convolutional neural networks (CNNs) based on encoder-decoder architecture have achieved tremendous success in various defect…
Multifunctional thin films in energy-related devices often must be electrically insulating where a single nanoscale defect can result in complete device-scale failure. Locating and characterizing such defects presents a fundamental problem…
This paper presents a comprehensive solution to address the critical challenge of liquid leaks in the oil and gas industry, leveraging advanced computer vision and deep learning methodologies. Employing You Only Look Once (YOLO) and…
Transformer-based object detectors (DETR) have shown significant performance across machine vision tasks, ultimately in object detection. This detector is based on a self-attention mechanism along with the transformer encoder-decoder…
CT images have been used to generate radiation therapy treatment plans for more than two decades. Dual-energy CT (DECT) has shown high accuracy in estimating electronic density or proton stopping-power maps used in treatment planning.…
The next major project of particle physics will be the International Linear Collider: a linear accelerator in which electrons and positrons will collide with energies of 500 to around 1000 billion electronvolts. The LPSC-Grenoble is…
In this paper we discuss the use of linked thermal and electrical network models to predict the behaviour of a complex silicon detector system. We use the silicon strip detector for the ATLAS Phase-II upgrade to demonstrate the application…
We present a deep learning, computer vision algorithm constructed for the purposes of identifying and classifying charged particles in camera image sensors. We apply our algorithm to data collected by the Distributed Electronic Cosmic-ray…
In this work, a simple and efficient thin ($50- 350\mu g/cm^2$) deuterated polyethylene target preparation method is described. The method of easy removal of thin targets from casting surface without using any cryogenic freezing has been…
The CALICE collaboration is currently developing an engineering prototype of an analog hadron calorimeter for a future linear collider detector. It is based on scintillating tiles that are individually read out by silicon photomultipliers.…
This paper introduces in full detail a methodology for the measurement of neutron yield and the necessary efficiency calibration, to be applied to the intensity measurement of neutron bursts where individual neutrons are not resolved in…
The CALICE collaboration is developing a granular electromagnetic calorimeter using (5-10) mm x 45 mm x 3 mm scintillator strips for a future linear collider experiment. Each scintillator strip is read out by using a Pixelated Photon…
TileCal is the hadronic calorimeter covering the most central region of the ATLAS experiment at the LHC. This sampling calorimeter uses iron plates as absorber and plastic scintillating tiles as the active material. A multi-faceted…
The e_LiBANS project aims at creating accelerator based compact neutron facilities for diverse interdisciplinary applications. After the successful setting up and characterization of a thermal neutron source based on a medical electron…
The online Data Quality Monitoring system (DQM) of the CMS electromagnetic calorimeter (ECAL) is a crucial operational tool that allows ECAL experts to quickly identify, localize, and diagnose a broad range of detector issues that would…
This paper presents mechanical R&D for the CALICE Silicon-tungsten electromagnetic calorimeter. After the physics ECAL prototype, tested in 2006 (DESY-CERN), 2007 (CERN), 2008 (FNAL) and before the design of different "modules 0" (barrel…
The Compact Linear Collider, CLIC, is a multi-TeV electron-positron collider proposed for construction at CERN. A detector model, CLICdet, that is suited for the experimental conditions at CLIC and is based on realistic performance, has…
This study presents a preliminary design and simulation of a thermal neutron diffractometer using the McStas Monte Carlo ray-tracing package. The simulated system is based on generalized instrument parameters, including typical collimator…
Recently, the performance of monocular depth estimation (MDE) has been significantly boosted with the integration of transformer models. However, the transformer models are usually computationally-expensive, and their effectiveness in…
Accurate structural analysis is essential to gain physical knowledge and understanding of atomic-scale processes in materials from atomistic simulations. However, traditional analysis methods often reach their limits when applied to…