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Träfflista för sökning "WFRF:(Lu L) ;mspu:(conferencepaper)"

Sökning: WFRF:(Lu L) > Konferensbidrag

  • Resultat 1-10 av 86
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1.
  • Aamodt, K., et al. (författare)
  • Alignment of the ALICE Inner Tracking System with cosmic-ray tracks
  • 2010
  • Ingår i: Journal of Instrumentation. - 1748-0221. ; 5
  • Konferensbidrag (refereegranskat)abstract
    • ALICE (A Large Ion Collider Experiment) is the LHC (Large Hadron Collider) experiment devoted to investigating the strongly interacting matter created in nucleus-nucleus collisions at the LHC energies. The ALICE ITS, Inner Tracking System, consists of six cylindrical layers of silicon detectors with three different technologies; in the outward direction: two layers of pixel detectors, two layers each of drift, and strip detectors. The number of parameters to be determined in the spatial alignment of the 2198 sensor modules of the ITS is about 13,000. The target alignment precision is well below 10 mu m in some cases (pixels). The sources of alignment information include survey measurements, and the reconstructed tracks from cosmic rays and from proton-proton collisions. The main track-based alignment method uses the Millepede global approach. An iterative local method was developed and used as well. We present the results obtained for the ITS alignment using about 10(5) charged tracks from cosmic rays that have been collected during summer 2008, with the ALICE solenoidal magnet switched off.
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2.
  • Zhang, S. N., et al. (författare)
  • The high energy cosmic-radiation detection (HERD) facility onboard China's Space Station
  • 2014
  • Ingår i: Proceedings of SPIE - The International Society for Optical Engineering. - : SPIE. - 9780819496126
  • Konferensbidrag (refereegranskat)abstract
    • The High Energy cosmic-Radiation Detection (HERD) facility is one of several space astronomy payloads of the cosmic lighthouse program onboard China's Space Station, which is planned for operation starting around 2020 for about 10 years. The main scientific objectives of HERD are indirect dark matter search, precise cosmic ray spectrum and composition measurements up to the knee energy, and high energy gamma-ray monitoring and survey. HERD is composed of a 3-D cubic calorimeter (CALO) surrounded by microstrip silicon trackers (STKs) from five sides except the bottom. CALO is made of about 104 cubes of LYSO crystals, corresponding to about 55 radiation lengths and 3 nuclear interaction lengths, respectively. The top STK microstrips of seven X-Y layers are sandwiched with tungsten converters to make precise directional measurements of incoming electrons and gamma-rays. In the baseline design, each of the four side SKTs is made of only three layers microstrips. All STKs will also be used for measuring the charge and incoming directions of cosmic rays, as well as identifying back scattered tracks. With this design, HERD can achieve the following performance: energy resolution of 1% for electrons and gamma-rays beyond 100 GeV, 20% for protons from 100 GeV to 1 PeV; electron/proton separation power better than 10-5; effective geometrical factors of >3 m2sr for electron and diffuse gamma-rays, >2 m2sr for cosmic ray nuclei. R and D is under way for reading out the LYSO signals with optical fiber coupled to image intensified CCD and the prototype of one layer of CALO. 
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3.
  • Kristan, M., et al. (författare)
  • The Eighth Visual Object Tracking VOT2020 Challenge Results
  • 2020
  • Ingår i: Computer Vision. - Cham : Springer International Publishing. - 9783030682378 ; , s. 547-601
  • Konferensbidrag (refereegranskat)abstract
    • The Visual Object Tracking challenge VOT2020 is the eighth annual tracker benchmarking activity organized by the VOT initiative. Results of 58 trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years. The VOT2020 challenge was composed of five sub-challenges focusing on different tracking domains: (i) VOT-ST2020 challenge focused on short-term tracking in RGB, (ii) VOT-RT2020 challenge focused on “real-time” short-term tracking in RGB, (iii) VOT-LT2020 focused on long-term tracking namely coping with target disappearance and reappearance, (iv) VOT-RGBT2020 challenge focused on short-term tracking in RGB and thermal imagery and (v) VOT-RGBD2020 challenge focused on long-term tracking in RGB and depth imagery. Only the VOT-ST2020 datasets were refreshed. A significant novelty is introduction of a new VOT short-term tracking evaluation methodology, and introduction of segmentation ground truth in the VOT-ST2020 challenge – bounding boxes will no longer be used in the VOT-ST challenges. A new VOT Python toolkit that implements all these novelites was introduced. Performance of the tested trackers typically by far exceeds standard baselines. The source code for most of the trackers is publicly available from the VOT page. The dataset, the evaluation kit and the results are publicly available at the challenge website (http://votchallenge.net ). 
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  • Felsberg, Michael, et al. (författare)
  • The Thermal Infrared Visual Object Tracking VOT-TIR2015 Challenge Results
  • 2015
  • Ingår i: Proceedings of the IEEE International Conference on Computer Vision. - : Institute of Electrical and Electronics Engineers (IEEE). - 9781467383905 ; , s. 639-651
  • Konferensbidrag (refereegranskat)abstract
    • The Thermal Infrared Visual Object Tracking challenge 2015, VOTTIR2015, aims at comparing short-term single-object visual trackers that work on thermal infrared (TIR) sequences and do not apply prelearned models of object appearance. VOT-TIR2015 is the first benchmark on short-term tracking in TIR sequences. Results of 24 trackers are presented. For each participating tracker, a short description is provided in the appendix. The VOT-TIR2015 challenge is based on the VOT2013 challenge, but introduces the following novelties: (i) the newly collected LTIR (Linköping TIR) dataset is used, (ii) the VOT2013 attributes are adapted to TIR data, (iii) the evaluation is performed using insights gained during VOT2013 and VOT2014 and is similar to VOT2015.
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