相关论文: Automated visual inspection of silicon detectors i…

Both the current upgrades to accelerator-based HEP detectors (e.g. ATLAS, CMS) and also future projects (e.g. CEPC, FCC) feature large-area silicon-based tracking detectors. We are investigating the feasibility of using CMOS foundries to…

The CMS detector is under construction for imminent operation at the Large Hadron Collider at CERN near Geneva, Switzerland. The installation and commissioning is performed in a surface hall. Thereafter, all the main heavy elements of the…

Reducing the incidence of surgical site infections (SSIs) is one of the objectives of the French nosocomial infection control program. Manual monitoring of SSIs is carried out each year by the hospital hygiene team and surgeons at the…

Formal verification of complex algorithms is challenging. Verifying their implementations goes beyond the state of the art of current automatic verification tools and usually involves intricate mathematical theorems. Certifying algorithms…

The Compact Muon Solenoid experiment at the Large Hadron Collider at CERN includes a silicon pixel detector as its innermost component. Its main task is the precise reconstruction of charged particles close to the primary interaction…

The CMS detector at the CERN LHC features a silicon pixel detector as its innermost subdetector. The original CMS pixel detector has been replaced with an upgraded pixel system (CMS Phase-1 pixel detector) in the extended year-end technical…

The testing and quality assurance of cryogenic superconducting detectors is a time- and labor-intensive process. As experiments deploy increasingly larger arrays of detectors, new methods are needed for performing this testing quickly.…

The Large Hadron Collider (LHC) experiments ATLAS and CMS have established hybrid pixel detectors as the instrument of choice for particle tracking and vertexing in high rate and radiation environments, as they operate close to the LHC…

The Framework is one of the subprojects of the Joint COntrols Project (JCOP), which is collaboration between the four LHC experiments and CERN. By sharing development, this will reduce the overall effort required to build and maintain the…

Cherenkov threshold detectors (XCET) are used for identifying particles in the experimental areas at CERN. These detectors observe Cherenkov light emitted by charged particles travelling inside a pressurized gas vessel. A key component of…

The series of upgrades to the Large Hadron Collider, culminating in the High Luminosity Large Hadron Collider, will enable a significant expansion of the physics program of the CMS experiment. However, the accelerator upgrades will also…

Machine-vision-based defect classification techniques have been widely adopted for automatic quality inspection in manufacturing processes. This article describes a general framework for classifying defects from high volume data batches…

Deep Learning is emerging as an effective technique to detect sophisticated cyber-attacks targeting Industrial Control Systems (ICSs). The conventional approach to detection in literature is to learn the "normal" behaviour of the system, to…

Fast, non-destructive and on-site quality control tools, mainly high sensitive imaging techniques, are important to assess the reliability of photovoltaic plants. To minimize the risk of further damages and electrical yield losses,…

There is strong theoretical motivation for the study of events with 2 same-sign leptons, jets, and missing transverse energy (MET) at the Large Hadron Collider (LHC). There are many compelling models, for instance, supersymmetry and extra…

For the Inner Tracking System 3 (ITS3) upgrade, the ALICE experiment at CERN requires monolithic active pixel sensors of dimensions up to 97~mm$\,\times\,$266~mm, occupying a large fraction of a 300 mm wafer. To manufacture such a…

In manufacturing processes, surface inspection is a key requirement for quality assessment and damage localization. Due to this, automated surface anomaly detection has become a promising area of research in various industrial inspection…

Capabilities and the number of vision-based models are increasing rapidly. And these vision models are now able to do more tasks like object detection, image classification, instance segmentation etc. with great accuracy. But models which…

Automated detection of defects in Printed Circuit Board (PCB) manufacturing using Solder Paste Inspection (SPI) and Automated Optical Inspection (AOI) machines can help improve operational efficiency and significantly reduce the need for…

Deep learning-based semiconductor defect inspection has gained traction in recent years, offering a powerful and versatile approach that provides high accuracy, adaptability, and efficiency in detecting and classifying nano-scale defects.…