相关论文: Automated visual inspection of silicon detectors i…
The control software of the CERN Compact Muon Solenoid experiment contains over 30,000 finite state machines. These state machines are organised hierarchically: commands are sent down the hierarchy and state changes are sent upwards. The…
The increasing need for automated visual monitoring and control for applications such as smart camera surveillance, traffic monitoring, and intelligent environments, necessitates the improvement of methods for visual active monitoring.…
The planned upgrade of the LHC accelerator at CERN, namely the high luminosity (HL) phase of the LHC (HL-LHC foreseen for 2023), will result in a more intense radiation environment than the present tracking system was designed for. The…
An important aspect of many particle accelerators is the constant evolution and frequent configuration changes that are needed to perform the experiments they are designed for. This often leads to the design of configurable software that…
The ATLAS detector at CERN's Large Hadron Collider (LHC) is equipped with a tracking system at its core (the Inner Detector, ID) consisting of silicon and gaseous straw tube detectors. The physics performance of the ID requires a precision…
To face the higher levels of radiation due to the 10-fold increase in integrated luminosity during the High-Luminosity LHC, the CMS detector will replace the current Calorimeter Endcap (CE) using the High-Granularity Calorimeter (HGCAL)…
With the rapid growth of display devices, quality inspection via machine vision technology has become increasingly important for flat-panel displays (FPD) industry. This paper discloses a novel visual inspection system for liquid crystal…
The rapid growth of the Industry 4.0 paradigm is increasing the pressure to develop effective automated monitoring systems. Artificial Intelligence (AI) is a convenient tool to improve the efficiency of industrial processes while reducing…
With its enormous number of produced neutrinos the LHC is a prime facility to study the behaviour of high-energy neutrinos. In this paper we propose a novel search strategy for identifying neutrino scattering via displaced appearing jets in…
Automated visual inspection in medical-device manufacturing faces unique challenges, including extremely low defect rates, limited annotated data, hardware restrictions on production lines, and the need for validated, explainable…
Vision systems, i.e., systems that allow to detect and track objects in images, have gained substantial importance over the past decades. They are used in quality assurance applications, e.g., for finding surface defects in products during…
The silicon systems of the Large Hadron Collider (LHC) detectors are briefly described. The complexity and diversity of the projects are illustrated by highlighting for discussion different components of the silicon systems in each…
A new tracking detector will be installed as part of the Phase-2 upgrade of the CMS detector for the high-luminosity LHC era. This tracking detector includes the Inner Tracker, equipped with silicon pixel sensor modules, and the Outer…
The design of an automatic visual inspection system is usually performed in two stages. While the first stage consists in selecting the most suitable hardware setup for highlighting most effectively the defects on the surface to be…
3D silicon sensors, where plasma micro-machining is used to etch deep narrow apertures in the silicon substrate to form electrodes of PIN junctions, represent possible solutions for inner pixel layers of the tracking detectors in high…
The detection and localization of quality-related problems in industrially mass-produced products has historically relied on manual inspection, which is costly and error-prone. Machine learning has the potential to replace manual handling.…
Hybrid silicon pixel detectors are currently used in the innermost tracking system of the Compact Muon Solenoid (CMS) experiment. Radiation tolerance up to fluences expected for a few years of running of the Large Hadron Collider (LHC) has…
Robot manipulation relying on learned object-centric descriptors became popular in recent years. Visual descriptors can easily describe manipulation task objectives, they can be learned efficiently using self-supervision, and they can…
There has been increasing interest in characterising the error behaviour of systems which contain deep learning models before deploying them into any safety-critical scenario. However, characterising such behaviour usually requires…
Strong lensing in galaxy clusters probes properties of dense cores of dark matter halos in mass, studies the distant universe at flux levels and spatial resolutions otherwise unavailable, and constrains cosmological models independently.…