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The one-shot multi-object tracking, which integrates object detection and ID embedding extraction into a unified network, has achieved groundbreaking results in recent years. However, current one-shot trackers solely rely on single-frame…

Computer Vision and Pattern Recognition · Computer Science 2021-12-14 Chao Liang , Zhipeng Zhang , Xue Zhou , Bing Li , Weiming Hu

The ATLAS inner detector comprises three different sub-detectors: the pixel detector, the silicon strip tracker, and the transition-radiation drift-tube tracker. The Insertable $B$-Layer, a new innermost pixel layer, was installed during…

High Energy Physics - Experiment · Physics 2017-12-08 ATLAS Collaboration

Reconstructing charged particle tracks is a fundamental task in modern collider experiments. The unprecedented particle multiplicities expected at the High-Luminosity Large Hadron Collider (HL-LHC) pose significant challenges for track…

High Energy Physics - Experiment · Physics 2025-12-16 Samuel Van Stroud , Philippa Duckett , Max Hart , Nikita Pond , Sébastien Rettie , Gabriel Facini , Tim Scanlon

Magnetic Particle Imaging is an emerging imaging modality through which it is possible to detect tracers containing superparamagnetic nanoparticles. The exposure of the particles to dynamic magnetic fields generates a non-linear response…

Numerical Analysis · Mathematics 2024-06-19 Vladyslav Gapyak , Thomas März , Andreas Weinmann

LHCb is the dedicated heavy flavour experiment at the Large Hadron Collider at CERN. The partially assembled silicon vertex locator (VELO) of the LHCb experiment has been tested in a beam test. The data from this beam test have been used to…

Instrumentation and Detectors · Physics 2008-11-26 M. Gersabeck , S. Viret , C. Parkes

Over the last two decades, scanning tunnelling microscopy (STM) has become one of the most important ways to investigate the structure of crystal surfaces. STM has helped achieve remarkable successes in surface science such as finding the…

Materials Science · Physics 2009-11-10 Cristian V. Ciobanu , Cristian Predescu

The purpose of this work is to examine the application of a deep learning model in event reconstruction of neutrino interactions. The challenges faced in event reconstruction include the placement of an accurate primary neutrino interaction…

Instrumentation and Detectors · Physics 2021-12-03 Zakaria Elkarghli

One of the most important problems of data processing in high energy and nuclear physics is the event reconstruction. Its main part is the track reconstruction procedure which consists in looking for all tracks that elementary particles…

Machine Learning · Computer Science 2019-10-02 Dmitriy Baranov , Sergey Mitsyn , Pavel Goncharov , Gennady Ososkov

The central arm spectrometers for the PHENIX experiment at the Relativistic Heavy Ion Collider have been designed for the optimization of particle identification in relativistic heavy ion collisions. The spectrometers present a challenging…

Nuclear Experiment · Physics 2009-11-07 J. T. Mitchell , PHENIX Collaboration

Inverse problems in imaging are typically ill-posed and are usually solved by employing regularized optimization techniques. The usage of appropriate constraints can restrict the solution space, thus making it feasible for a reconstruction…

Image and Video Processing · Electrical Eng. & Systems 2025-11-14 Jasleen Birdi , Tamal Majumder , Debanjan Halder , Muskan Kularia , Kedar Khare

CMOS pixel sensors (CPS) represent a novel technological approach to building charged particle detectors. CMOS processes allow to integrate a sensing volume and readout electronics in a single silicon die allowing to build sensors with a…

This report reviews methods of pattern recognition and event reconstruction used in modern high energy physics experiments. After a brief introduction into general concepts of particle detectors and statistical evaluation, different…

Data Analysis, Statistics and Probability · Physics 2009-11-10 Rainer Mankel

Previous state-of-the-art real-time object detectors have been reported on GPUs which are extremely expensive for processing massive data and in resource-restricted scenarios. Therefore, high efficiency object detectors on CPU-only devices…

Computer Vision and Pattern Recognition · Computer Science 2020-09-10 Chen Chen , Mengyuan Liu , Xiandong Meng , Wanpeng Xiao , Qi Ju

Object detection is a fundamental task for robots to operate in unstructured environments. Today, there are several deep learning algorithms that solve this task with remarkable performance. Unfortunately, training such systems requires…

Computer Vision and Pattern Recognition · Computer Science 2021-06-30 Federico Ceola , Elisa Maiettini , Giulia Pasquale , Lorenzo Rosasco , Lorenzo Natale

A unified method for three-dimensional reconstruction of objects from transmission images collected at multiple illumination directions is described. The method may be applicable to experimental conditions relevant to absorption-based,…

Medical Physics · Physics 2022-12-07 Timur E. Gureyev , Hamish G. Brown , Harry M. Quiney , Leslie J. Allen

High-energy physics is facing increasingly computational challenges in real-time event reconstruction for the near-future high-luminosity era. Using the LHCb vertex detector as a use-case, we explore a new algorithm for particle track…

Tiny object detection is one of the key challenges in the field of object detection. The performance of most generic detectors dramatically decreases in tiny object detection tasks. The main challenge lies in extracting effective features…

Computer Vision and Pattern Recognition · Computer Science 2024-10-01 Bing Cao , Haiyu Yao , Pengfei Zhu , Qinghua Hu

Convolutional networks for single-view object reconstruction have shown impressive performance and have become a popular subject of research. All existing techniques are united by the idea of having an encoder-decoder network that performs…

Computer Vision and Pattern Recognition · Computer Science 2019-05-10 Maxim Tatarchenko , Stephan R. Richter , René Ranftl , Zhuwen Li , Vladlen Koltun , Thomas Brox

We propose a novel method to accurately reconstruct a set of images representing a single scene from few linear multi-view measurements. Each observed image is modeled as the sum of a background image and a foreground one. The background…

Computer Vision and Pattern Recognition · Computer Science 2013-09-19 Gilles Puy , Pierre Vandergheynst