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Sökning: WFRF:(Chen Kaiqi)

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1.
  • Chen, Kaiqi, et al. (författare)
  • EC-Earth Simulations Reveal Enhanced Inter-Hemispheric Thermal Contrast During the Last Interglacial Further Intensified the Indian Monsoon
  • 2022
  • Ingår i: Geophysical Research Letters. - 0094-8276 .- 1944-8007. ; 49:6
  • Tidskriftsartikel (refereegranskat)abstract
    • Paleoclimate proxy data indicate a stronger Indian summer monsoon (ISM) during the Last Interglacial (LIG) than in the present day. This is largely attributed to orbital forcing induced high seasonal and latitudinal insolation anomalies in the Northern Hemisphere during LIG. According to the general circulation model EC-Earth3, the simulated ISM rainfall is increased by approximately 28% during the LIG compared to the pre-industrial period as a result of the orbital forcing and the amplified land-sea contrast due to both local and remote ocean feedbacks. Although the LIG is often portrayed as a potential analogue of future warmer climates, our study suggests that the enhanced inter-hemispheric thermal gradient during the LIG strengthened the ISM, in opposition to the observed weakening of ISM under present-day warming.
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2.
  • Kristan, Matej, et al. (författare)
  • The Visual Object Tracking VOT2013 challenge results
  • 2013
  • Ingår i: 2013 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCVW). - : IEEE. - 9781479930227 ; , s. 98-111
  • Konferensbidrag (refereegranskat)abstract
    • Visual tracking has attracted a significant attention in the last few decades. The recent surge in the number of publications on tracking-related problems have made it almost impossible to follow the developments in the field. One of the reasons is that there is a lack of commonly accepted annotated data-sets and standardized evaluation protocols that would allow objective comparison of different tracking methods. To address this issue, the Visual Object Tracking (VOT) workshop was organized in conjunction with ICCV2013. Researchers from academia as well as industry were invited to participate in the first VOT2013 challenge which aimed at single-object visual trackers that do not apply pre-learned models of object appearance (model-free). Presented here is the VOT2013 benchmark dataset for evaluation of single-object visual trackers as well as the results obtained by the trackers competing in the challenge. In contrast to related attempts in tracker benchmarking, the dataset is labeled per-frame by visual attributes that indicate occlusion, illumination change, motion change, size change and camera motion, offering a more systematic comparison of the trackers. Furthermore, we have designed an automated system for performing and evaluating the experiments. We present the evaluation protocol of the VOT2013 challenge and the results of a comparison of 27 trackers on the benchmark dataset. The dataset, the evaluation tools and the tracker rankings are publicly available from the challenge website(1).
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