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Träfflista för sökning "WFRF:(Liu Xiang) ;mspu:(conferencepaper)"

Sökning: WFRF:(Liu Xiang) > Konferensbidrag

  • Resultat 1-10 av 14
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1.
  • Kristan, Matej, et al. (författare)
  • The Ninth Visual Object Tracking VOT2021 Challenge Results
  • 2021
  • Ingår i: 2021 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCVW 2021). - : IEEE COMPUTER SOC. - 9781665401913 ; , s. 2711-2738
  • Konferensbidrag (refereegranskat)abstract
    • The Visual Object Tracking challenge VOT2021 is the ninth annual tracker benchmarking activity organized by the VOT initiative. Results of 71 trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in recent years. The VOT2021 challenge was composed of four sub-challenges focusing on different tracking domains: (i) VOT-ST2021 challenge focused on short-term tracking in RGB, (ii) VOT-RT2021 challenge focused on "real-time" short-term tracking in RGB, (iii) VOT-LT2021 focused on long-term tracking, namely coping with target disappearance and reappearance and (iv) VOT-RGBD2021 challenge focused on long-term tracking in RGB and depth imagery. The VOT-ST2021 dataset was refreshed, while VOT-RGBD2021 introduces a training dataset and sequestered dataset for winner identification. The source code for most of the trackers, the datasets, the evaluation kit and the results along with the source code for most trackers are publicly available at the challenge website(1).
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  • Kristanl, Matej, et al. (författare)
  • The Seventh Visual Object Tracking VOT2019 Challenge Results
  • 2019
  • Ingår i: 2019 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCVW). - : IEEE COMPUTER SOC. - 9781728150239 ; , s. 2206-2241
  • Konferensbidrag (refereegranskat)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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  • Xiang, Yiqiang, et al. (författare)
  • Risk Analysis and Assessment of Public Safety of Submerged Floating Tunnel
  • 2010
  • Ingår i: ISAB-2010 - FIRST INTERNATIONAL SYMPOSIUM ON ARCHIMEDES BRIDGE. - : Elsevier BV. ; , s. 117-125
  • Konferensbidrag (refereegranskat)abstract
    •  Based on the structural characteristics and preliminary design of submerged floating tunnel (SFT) prototype in Qiandao Lake, this paper gives the risk index system of public safety of SFT and risk assessment methods by analyzing different impact factors of SFT public safety. Moreover, the public safety risk is evaluated during construction and operation of SFT prototype in Qiandao Lake by the presented analytic hierarchy process method. The results show that in spite of facing many technical problems and potential risks, these potential risks of SFT can be controlled or reduced to a minimum level with the help of reasonable design and certain measures
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  • Hou, Junyao, et al. (författare)
  • Abstraction-Based Synthesis of Controllers for Approximate Opacity
  • 2023
  • Ingår i: 2023 62nd IEEE Conference on Decision and Control, CDC 2023. - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 7930-7936
  • Konferensbidrag (refereegranskat)abstract
    • Opacity is an important information-flow security property which characterizes the plausible deniability of certain 'secret behaviors' in dynamical systems. In this paper, we study the problem of synthesizing controllers enforcing a notion of opacity over discrete-time control systems with continuous state sets. In this paper, we develop an abstraction-based approach to tackle the controller synthesis problem. Specifically, we adopt a notion of approximate opacity which is suitable for continuous-space control systems. We propose a notion of approximate initial-state opacity preserving alternating simulation relation which characterizes the closeness between two systems in terms of opacity preservation. We show that, based on this new notion of system relation, one can synthesize an opacity-enforcing controller for the abstract system which is finite and then refine it back to enforce opacity over the original control system. Finally, we present a method for constructing opacity-preserving finite abstractions for discrete-time control systems under some stability properties. Our results are illustrated on a two-room temperature control problem.
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  • Liu, Xinyu, et al. (författare)
  • Vehicle trajectory prediction through manual setting and machine learning
  • 2022
  • Ingår i: ISCTT 2022 - 7th International Conference on Information Science, Computer Technology and Transportation. ; , s. 612-616
  • Konferensbidrag (refereegranskat)abstract
    • The prediction of vehicle trajectory is an important step in safe driving. The relative positions or speeds of vehicles affect the interactions between them, which in turn produce predictions of trajectories. Through the trajectory prediction of each vehicle to form a complete safe driving environment. This paper will be divided into two parts for vehicle track, namely manual setting and machine learning. The advantage of manual setting is that it is convenient to observe the characteristics and then make other vehicles follow the corresponding behaviour. However, the disadvantage is that the characteristics that can be observed are incomplete, which makes the experimental error relatively large. The advantage of machine learning is that through previous experience to make all vehicles change in the corresponding situation. Through previous experience to make all vehicles change in the corresponding situation. An effective extraction and addition of the original data is helpful to reduce the final error. Our code base can be found in https://github.com/RR30/CIS_multi_vehicle_prediction/tree/Xinyu.
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10.
  • Liu, Yi, et al. (författare)
  • Laser without population inversion of nitrogen ions pumped by femtosecond pulses
  • 2019
  • Ingår i: CLEO : QELS_Fundamental Science, CLEO_QELS 2019 - QELS_Fundamental Science, CLEO_QELS 2019. - 9781557528209
  • Konferensbidrag (refereegranskat)abstract
    • We attribute the mechanism of "lasing" action of nitrogen ions pumped by femtosecond IR pulses to a laser without inversion scheme. Numerical simulations reproduce well the temporal dynamics and pressure dependence of the emission.
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