Related papers: Progress towards the Detailed Baseline Design for …

We report on the electrical and functional characterization of 3D Double-side, Double-Type-Column (3D- DDTC) detectors fabricated on p-type substrates. Results relevant to detectors in the diode, strip and pixel configurations are…

Most generic object detectors are mainly built for standard object detection tasks such as COCO and PASCAL VOC. They might not work well and/or efficiently on tasks of other domains consisting of images that are visually different from…

The ATLAS detector has to undergo significant updates at the end of the current decade, in order to withstand the increased occupancy and radiation damage that will be produced by the high-luminosity upgrade of the Large Hadron Collider. In…

In order to fully exploit the physics potential of the future high energy e+e- linear collider, a Vertex Tracker able to provide particle track extrapolation with very high resolution is needed. Hybrid Si pixel sensors are an attractive…

We introduce BIDCD -- the Bosch Industrial Depth Completion Dataset. BIDCD is a new RGBD dataset of metallic industrial objects, collected with a depth camera mounted on a robotic manipulator. The main purpose of this dataset is to…

Crack detection plays a crucial role in civil infrastructures, including inspection of pavements, buildings, etc., and deep learning has significantly advanced this field in recent years. While numerous technical and review papers exist in…

Road damage detection and assessment are crucial components of infrastructure maintenance. However, current methods often struggle with detecting multiple types of road damage in a single image, particularly at varying scales. This is due…

Recent advancements in LiDAR-based 3D object detection have significantly accelerated progress toward the realization of fully autonomous driving in real-world environments. Despite achieving high detection performance, most of the…

This is part of a document, which is devoted to the developments of pixel detectors in the context of the International Linear Collider. From the early developments of the MIMOSAs to the proposed DotPix I recall some of the major…

Calorimeters with silicon detectors have many unique features and are proposed for several world-leading experiments. We describe the R&D program of the large scale detector element with up to 12 000 readout channels for the International…

We report a concept low gain avalanche diode (LGAD) detector to be integrated into TOPSiDE, which is being developed for EIC (Electron-Ion Collider) project. The LGAD detector will be taking its place to resolve requirement of…

In the past 10 years, two design innovations, the introduction of low internal gain (LGAD) and of resistive read-out (RSD), have radically changed the performance of silicon detectors. The LGAD mechanism, increasing the signal-to-noise…

The aim of surface defect detection is to identify and localise abnormal regions on the surfaces of captured objects, a task that's increasingly demanded across various industries. Current approaches frequently fail to fulfil the extensive…

This paper synthesizes recent advances in the econometrics of difference-in-differences (DiD) and provides concrete recommendations for practitioners. We begin by articulating a simple set of ``canonical'' assumptions under which the…

Infrared small target detection (ISTD) faces two major challenges: a lack of discernible target texture and severe background clutter, which results in the background obscuring the target. To enhance targets and suppress backgrounds, we…

In the last years many results in the area of semidefinite programming were obtained for invariant (finite dimensional, or infinite dimensional) semidefinite programs - SDPs which have symmetry. This was done for a variety of problems and…

The successful running of the large area Silicon trackers of ATLAS and CMS at LHC, and the ongoing R&D for the upgrade of these tracking systems, in various stages, over this decade, are a full proof of this technology and of its still…

We present Deeply Supervised Object Detector (DSOD), a framework that can learn object detectors from scratch. State-of-the-art object objectors rely heavily on the off-the-shelf networks pre-trained on large-scale classification datasets…

In the context of Just-In-Time Software Defect Prediction (JIT-SDP), Concept drift (CD) can occur due to changes in the software development process, the complexity of the software, or changes in user behavior that may affect the stability…

Defocus blur detection (DBD) separates in-focus and out-of-focus regions in an image. Previous approaches mistakenly mistook homogeneous areas in focus for defocus blur regions, likely due to not considering the internal factors that cause…