Related papers: Progress towards the Detailed Baseline Design for …
The correct modeling of $e^+e^-$ collision events at the International Linear Collider (ILC), as well as the response of a collider detector like the Silicon Detector (SiD), is crucial to evaluating the expected sensitivity to key…
Urban-oriented autonomous vehicles require a reliable perception technology to tackle the high amount of uncertainties. The recently introduced compact 3D LIDAR sensor offers a surround spatial information that can be exploited to enhance…
Structure-based drug design (SBDD) stands at the forefront of drug discovery, emphasizing the creation of molecules that target specific binding pockets. Recent advances in this area have witnessed the adoption of deep generative models and…
As the popularity of iris recognition systems increases, the importance of effective security measures against presentation attacks becomes paramount. This work presents an overview of the most important advances in the area of iris…
Object detection models trained on a source domain often exhibit significant performance degradation when deployed in unseen target domains, due to various kinds of variations, such as sensing conditions, environments and data…
With the broadening landscape of proposals for future Higgs, top and electroweak physics factories, detector diversity as well as the reach and depth of physics analysis increase. One emerging topic of renewed interest is particle…
In this paper, we address the design of lightweight deep learning-based edge detection. The deep learning technology offers a significant improvement on the edge detection accuracy. However, typical neural network designs have very high…
The development of the Forward Spectator Detector (FSD) for the CBM experiment represents a crucial step toward successful realization of the CBM physics program - understanding of highly compressed nuclear matter at the forthcoming FAIR…
Line segment detection is a fundamental low-level task in computer vision, and improvements in this task can impact more advanced methods that depend on it. Most new methods developed for line segment detection are based on Convolutional…
We are on the way to obtaining multi-dimensional "pictures" of the proton. The field is bursting with activities, both from the theoretical and experimental side. A brief selection of important achievements of the last years and open…
Edge detection is a fundamental problem in different computer vision tasks. Recently, edge detection algorithms achieve satisfying improvement built upon deep learning. Although most of them report favorable evaluation scores, they often…
Industrial defect detection is vital for upholding product quality across contemporary manufacturing systems. As the expectations for precision, automation, and scalability intensify, conventional inspection approaches are increasingly…
Silicon Drift Detectors (SDD) equip the two central layers of the Inner Tracking System of the ALICE experiment at the LHC. Main results of systematic studies of detector performance including noise, gain, drift speed and charge collection…
Depth estimation is a fundamental task in 3D computer vision, crucial for applications such as 3D reconstruction, free-viewpoint rendering, robotics, autonomous driving, and AR/VR technologies. Traditional methods relying on hardware…
We are developing position sensitive silicon detectors (PSDs) which have an electrode at each of four corners so that incident position of a charged particle can be obtained with signal from the electrodes. It is expected that the position…
3D object detection aims to predict object centers, dimensions, and rotations from LiDAR point clouds. Despite its simplicity, LiDAR captures only the near side of objects, making center-based detectors prone to poor localization accuracy…
Detecting and segmenting salient objects from natural scenes, often referred to as salient object detection, has attracted great interest in computer vision. While many models have been proposed and several applications have emerged, a deep…
We report on recent progress and next steps in the design of the proposed MATHUSLA Long Lived Particle (LLP) detector for the HL-LHC as part of the Snowmass 2021 process. Our understanding of backgrounds has greatly improved, aided by…
In this Snowmass contribution we present a comprehensive status update on the progress and plans for the proposed CODEX-b detector, intended to search for long-lived particles beyond the Standard Model. We review the physics case for the…
The development of CMOS pixel sensors with column parallel read-out and integrated zero-suppression has resulted in a full size, nearly 1 Megapixel, prototype with ~100 \mu s read-out time. Its performances are quite close to the ILD vertex…