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QCD-jets at the LHC are described by simple physics principles. We show how super-resolution generative networks can learn the underlying structures and use them to improve the resolution of jet images. We test this approach on massless…

High Energy Physics - Phenomenology · Physics 2021-12-03 Pierre Baldi , Lukas Blecher , Anja Butter , Julian Collado , Jessica N. Howard , Fabian Keilbach , Tilman Plehn , Gregor Kasieczka , Daniel Whiteson

The low resolution of objects of interest in aerial images makes pedestrian detection and action detection extremely challenging tasks. Furthermore, using deep convolutional neural networks to process large images can be demanding in terms…

Computer Vision and Pattern Recognition · Computer Science 2018-07-17 Amir Soleimani , Nasser M. Nasrabadi

We consider the problem in Synthetic Aperture RADAR (SAR) of identifying and classifying objects located on the ground by means of Convolutional Neural Networks (CNNs). Specifically, we adopt a single scattering approximation to classify…

Computer Vision and Pattern Recognition · Computer Science 2025-08-07 Romina Gaburro , Patrick Healy , Shraddha Naidu , Clifford Nolan

Top quarks, produced in large numbers at the Large Hadron Collider, have a complex detector signature and require special reconstruction techniques. The most common decay mode, the "all-jet" channel, results in a 6-jet final state which is…

High Energy Physics - Experiment · Physics 2022-07-18 Michael James Fenton , Alexander Shmakov , Ta-Wei Ho , Shih-Chieh Hsu , Daniel Whiteson , Pierre Baldi

This Letter describes a search for narrowly resonant new physics using a machine-learning anomaly detection procedure that does not rely on a signal simulations for developing the analysis selection. Weakly supervised learning is used to…

High Energy Physics - Experiment · Physics 2022-01-12 ATLAS Collaboration

In clinical CT system, the x-ray tube emits polychromatic x-rays, and the x-ray detectors operate in the current-integrating mode. This physical process is accurately described by an energy-dependent non-linear integral equation. However,…

Medical Physics · Physics 2020-06-23 Wenxiang Cong , Bruno De Man , Ge Wang

Following the success of machine vision systems for on-line automated quality control and inspection processes, an object recognition solution is presented in this work for two different specific applications, i.e., the detection of quality…

Computer Vision and Pattern Recognition · Computer Science 2022-07-01 Kai Yao , Alberto Ortiz , Francisco Bonnin-Pascual

The performance of jet finding using only charged tracks in CMS has been investigated. Different jet algorithms have been applied to QCD di-jet events, to hadronic tt multi-jet events and on Z+jets events. Results using jets made with…

High Energy Physics - Experiment · Physics 2014-11-18 Paolo Azzurri

3D time-of-flight (ToF) imaging is used in a variety of applications such as augmented reality (AR), computer interfaces, robotics and autonomous systems. Single-photon avalanche diodes (SPADs) are one of the enabling technologies providing…

Image and Video Processing · Electrical Eng. & Systems 2021-10-13 Germán Mora-Martín , Alex Turpin , Alice Ruget , Abderrahim Halimi , Robert Henderson , Jonathan Leach , Istvan Gyongy

Deciphering the complex information contained in jets produced in collider events requires a physical organization of the jet data. We introduce two-particle correlations (2PCs) by pairing individual particles as the initial jet…

High Energy Physics - Phenomenology · Physics 2020-07-01 Kai-Feng Chen , Yang-Ting Chien

Single particle imaging (SPI) at X-ray free electron lasers (XFELs) is particularly well suited to determine the 3D structure of particles in their native environment. For a successful reconstruction, diffraction patterns originating from a…

Data Analysis, Statistics and Probability · Physics 2021-12-17 Dameli Assalauova , Alexandr Ignatenko , Fabian Isensee , Sergey Bobkov , Darya Trofimova , Ivan A. Vartanyants

This technical note describes the design and modular implementation of a one-dimensional convolutional neural network (1D CNN) adapted from residual networks (ResNet), developed for photometric regression tasks with an emphasis on low star…

Instrumentation and Methods for Astrophysics · Physics 2025-06-04 Po-Chieh Yu

Jet interactions in a hot QCD medium created in heavy-ion collisions are conventionally assessed by measuring the modification of the distributions of jet observables with respect to the proton-proton baseline. However, the steeply falling…

High Energy Physics - Phenomenology · Physics 2021-04-01 Yi-Lun Du , Daniel Pablos , Konrad Tywoniuk

Recently, many Convolution Neural Networks (CNN) have been successfully employed in bitemporal SAR image change detection. However, most of the existing networks are too heavy and occupy a large volume of memory for storage and calculation.…

Image and Video Processing · Electrical Eng. & Systems 2020-06-23 Rongfang Wang , Fan Ding , Licheng Jiao , Jia-Wei Chen , Bo Liu , Wenping Ma , Mi Wang

A unified deep neural network, denoted the multi-scale CNN (MS-CNN), is proposed for fast multi-scale object detection. The MS-CNN consists of a proposal sub-network and a detection sub-network. In the proposal sub-network, detection is…

Computer Vision and Pattern Recognition · Computer Science 2016-07-26 Zhaowei Cai , Quanfu Fan , Rogerio S. Feris , Nuno Vasconcelos

Many Beyond the Standard Model searches at ATLAS employ jets to simplify event reconstruction. These jets cluster particle shower products into calculable objects, which are then used to obtain information about parent particles. Large-R (R…

High Energy Physics - Experiment · Physics 2025-07-23 Sophie Kadan , Evelyn Thomson

The radiation pattern within high energy quark- and gluon-initiated jets (jet substructure) is used extensively as a precision probe of the strong force as well as an environment for optimizing event generators with numerous applications in…

High Energy Physics - Experiment · Physics 2023-09-15 The H1 collaboration , V. Andreev , M. Arratia , A. Baghdasaryan , A. Baty , K. Begzsuren , A. Bolz , V. Boudry , G. Brandt , D. Britzger , A. Buniatyan , L. Bystritskaya , A. J. Campbell , K. B. Cantun Avila , K. Cerny , V. Chekelian , Z. Chen , J. G. Contreras , J. Cvach , J. B. Dainton , K. Daum , A. Deshpande , C. Diaconu , A. Drees , G. Eckerlin , S. Egli , E. Elsen , L. Favart , A. Fedotov , J. Feltesse , M. Fleischer , A. Fomenko , C. Gal , J. Gayler , L. Goerlich , N. Gogitidze , M. Gouzevitch , C. Grab , T. Greenshaw , G. Grindhammer , D. Haidt , R. C. W. Henderson , J. Hessler , J. Hladký , D. Hoffmann , R. Horisberger , T. Hreus , F. Huber , P. M. Jacobs , M. Jacquet , T. Janssen , A. W. Jung , J. Katzy , C. Kiesling , M. Klein , C. Kleinwort , H. T. Klest , R. Kogler , P. Kostka , J. Kretzschmar , D. Krücker , K. Krüger , M. P. J. Landon , W. Lange , P. Laycock , S. H. Lee , S. Levonian , W. Li , J. Lin , K. Lipka , B. List , J. List , B. Lobodzinski , O. R. Long , E. Malinovski , H. -U. Martyn , S. J. Maxfield , A. Mehta , A. B. Meyer , J. Meyer , S. Mikocki , V. M. Mikuni , M. M. Mondal , K. Müller , B. Nachman , Th. Naumann , P. R. Newman , C. Niebuhr , G. Nowak , J. E. Olsson , D. Ozerov , S. Park , C. Pascaud , G. D. Patel , E. Perez , A. Petrukhin , I. Picuric , D. Pitzl , R. Polifka , S. Preins , V. Radescu , N. Raicevic , T. Ravdandorj , P. Reimer , E. Rizvi , P. Robmann , R. Roosen , A. Rostovtsev , M. Rotaru , D. P. C. Sankey , M. Sauter , E. Sauvan , S. Schmitt , B. A. Schmookler , G. Schnell , L. Schoeffel , A. Schöning , F. Sefkow , S. Shushkevich , Y. Soloviev , P. Sopicki , D. South , A. Specka , M. Steder , B. Stella , U. Straumann , C. Sun , T. Sykora , P. D. Thompson , F. Torales Acosta , D. Traynor , B. Tseepeldorj , Z. Tu , G. Tustin , A. Valkárová , C. Vallée , P. Van Mechelen , D. Wegener , E. Wünsch , J. Žáček , J. Zhang , Z. Zhang , R. Žlebčík , H. Zohrabyan , F. Zomer

A Compton/Pair telescope, designed to provide spectral resolved images of cosmic photons from sub-MeV to GeV energies, records a wealth of data in a combination of tracking detector and calorimeter. Onboard event classification can be…

Instrumentation and Methods for Astrophysics · Physics 2024-11-05 Jan Peter Lommler , Uwe Oberlack

State-of-the-art object detection approaches such as Fast/Faster R-CNN, SSD, or YOLO have difficulties detecting dense, small targets with arbitrary orientation in large aerial images. The main reason is that using interpolation to align…

Computer Vision and Pattern Recognition · Computer Science 2020-06-01 Wentong Liao , Xiang Chen , Jingfeng Yang , Stefan Roth , Michael Goesele , Michael Ying Yang , Bodo Rosenhahn

Interpreting the spectral energy distributions (SEDs) of astrophysical objects with physically motivated models is computationally expensive. These models require solving coupled differential equations in high-dimensional parameter spaces,…

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