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Träfflista för sökning "WFRF:(Liu Jin ming) ;pers:(Wang Qiang)"

Search: WFRF:(Liu Jin ming) > Wang Qiang

  • Result 1-7 of 7
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1.
  • Kristanl, Matej, et al. (author)
  • The Seventh Visual Object Tracking VOT2019 Challenge Results
  • 2019
  • In: 2019 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCVW). - : IEEE COMPUTER SOC. - 9781728150239 ; , s. 2206-2241
  • Conference paper (peer-reviewed)abstract
    • The Visual Object Tracking challenge VOT2019 is the seventh annual tracker benchmarking activity organized by the VOT initiative. Results of 81 trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years. The evaluation included the standard VOT and other popular methodologies for short-term tracking analysis as well as the standard VOT methodology for long-term tracking analysis. The VOT2019 challenge was composed of five challenges focusing on different tracking domains: (i) VOT-ST2019 challenge focused on short-term tracking in RGB, (ii) VOT-RT2019 challenge focused on "real-time" short-term tracking in RGB, (iii) VOT-LT2019 focused on long-term tracking namely coping with target disappearance and reappearance. Two new challenges have been introduced: (iv) VOT-RGBT2019 challenge focused on short-term tracking in RGB and thermal imagery and (v) VOT-RGBD2019 challenge focused on long-term tracking in RGB and depth imagery. The VOT-ST2019, VOT-RT2019 and VOT-LT2019 datasets were refreshed while new datasets were introduced for VOT-RGBT2019 and VOT-RGBD2019. The VOT toolkit has been updated to support both standard short-term, long-term tracking and tracking with multi-channel imagery. 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(1).
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2.
  • Kristan, Matej, et al. (author)
  • The Sixth Visual Object Tracking VOT2018 Challenge Results
  • 2019
  • In: Computer Vision – ECCV 2018 Workshops. - Cham : Springer Publishing Company. - 9783030110086 - 9783030110093 ; , s. 3-53
  • Conference paper (peer-reviewed)abstract
    • The Visual Object Tracking challenge VOT2018 is the sixth annual tracker benchmarking activity organized by the VOT initiative. Results of over eighty trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years. The evaluation included the standard VOT and other popular methodologies for short-term tracking analysis and a “real-time” experiment simulating a situation where a tracker processes images as if provided by a continuously running sensor. A long-term tracking subchallenge has been introduced to the set of standard VOT sub-challenges. The new subchallenge focuses on long-term tracking properties, namely coping with target disappearance and reappearance. A new dataset has been compiled and a performance evaluation methodology that focuses on long-term tracking capabilities has been adopted. The VOT toolkit has been updated to support both standard short-term and the new long-term tracking subchallenges. 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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3.
  • Kristan, Matej, et al. (author)
  • The Visual Object Tracking VOT2017 challenge results
  • 2017
  • In: 2017 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCVW 2017). - : IEEE. - 9781538610343 ; , s. 1949-1972
  • Conference paper (peer-reviewed)abstract
    • The Visual Object Tracking challenge VOT2017 is the fifth annual tracker benchmarking activity organized by the VOT initiative. Results of 51 trackers are presented; many are state-of-the-art published at major computer vision conferences or journals in recent years. The evaluation included the standard VOT and other popular methodologies and a new "real-time" experiment simulating a situation where a tracker processes images as if provided by a continuously running sensor. 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 VOT2017 goes beyond its predecessors by (i) improving the VOT public dataset and introducing a separate VOT2017 sequestered dataset, (ii) introducing a realtime tracking experiment and (iii) releasing a redesigned toolkit that supports complex experiments. The dataset, the evaluation kit and the results are publicly available at the challenge website(1).
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4.
  • Liu, Ming, et al. (author)
  • A High-End Reconfigurable Computation Platform for Nuclear and Particle Physics Experiments
  • 2011
  • In: Computing in science & engineering (Print). - 1521-9615 .- 1558-366X. ; 13:2, s. 52-63
  • Journal article (peer-reviewed)abstract
    • A high-performance computation platform based on field-programmable gate arrays targets nuclear and particle physics experiment applications. The system can be constructed or scaled into a supercomputer-equivalent size for detector data processing by inserting compute nodes into advanced telecommunications computing architecture (ATCA) crates. Among the case study results are that one ATCA crate can provide a computation capability equivalent to hundreds of commodity PCs for Hades online particle track reconstruction and Cherenkov ring recognition.
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5.
  • Liu, Ming, et al. (author)
  • ATCA-based Computation Platform for Data Acquisition and Triggering in Particle Physics Experiments
  • 2008
  • In: 2008 INTERNATIONAL CONFERENCE ON FIELD PROGRAMMABLE AND LOGIC APPLICATIONS, VOLS 1 AND 2. ; , s. 287-292
  • Conference paper (peer-reviewed)abstract
    • An ATCA-based computation platform for data acquisition and trigger applications in nuclear and particle physics experiments has been developed. Each Compute Node (CN) which appears as a Field Replaceable Unit (FRU) in an ATCA shelf, features 5 Xilinx Virtex-4 FX60 FPGAs and up to 10 GBytes DDR2 memory. Connectivity is provided with 8 optical links and 5 Gigabit Ethernet ports, which are mounted on each board to receive data from detectors and forward results to outer shelves or PC farms with attached mass storage. Fast point-to-point on-board interconnections between FPGAs as well as the full-mesh shelf backplane provide flexibility and high bandwidth to partition algorithms and correlate results among them. The system represents a highly reconfigurable and scalable solution for multiple applications.
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6.
  • Liu, Ming, et al. (author)
  • Trigger algorithm development on FPGA-based Compute Nodes
  • 2009
  • In: 2009 16th IEEE-NPSS Real Time Conference. - New York : IEEE. - 9781424457960 ; , s. 478-484
  • Conference paper (peer-reviewed)abstract
    • Based on the ATCA computation architecture and Compute Nodes (CN), investigation and implementation work has been being executed for HADES and PANDA trigger algorithms. We present our designs for HADES track reconstruction processing, Cherenkov ring recognition, Time-Of-Flight processing, electromagnetic shower recognition.. and the PANDA straw tube tracking algorithm. They will appear as co-processors in the uniform system design to undertake the detector-specific computing. The algorithm principles will be explained and hardware designs are described in the paper. The current progress reveals the feasibility to implement these algorithms on FPGAs. Also experimental results demonstrate the performance speedup when compared to alternative software solutions, as well as the potential capability of high-speed parallel/pipelined processing in Data Acquisition and Trigger systems.
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7.
  • Wang, Qiang, et al. (author)
  • Hardware/Software Co-design of an ATCA-based Computation Platform for Data Acquisition and Triggering
  • 2009
  • In: 16th IEEE NPSS Real Time Conference. - 9781424457960 ; , s. 485-489
  • Conference paper (peer-reviewed)abstract
    • An ATCA-based computation platform for data acquisition and trigger(TDAQ) applications has been developed for multiple future projects such its PANDA. HADES, and BESIII. Each Compute Node (CN) appears as one (if the fourteen Field Replaceable Units (FRU) in an ATCA shelf, which in total features a high performance of 1890 Clips inter-FPGA on-board channels, 1456 Gbps inter-board backplane connections, 728 Gbps full-duplex optical links, 70 Gbps Ethernet. 140 GBytes DDR2 SDRAM. and all computing resources of 70 Xilinx Virtex-4 FX60 FPGAs. Corresponding to (the system architecture, a hardware/software co-design approach is proposed to ease and accelerate the development for different experiments. In the uniform system design. application-specific computation is to be implemented as customized hardware co-processors, while the embedded PowerPC processor takes charge of flexible slow controls and transmission protocol processing.
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  • Result 1-7 of 7

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