Showing 781 - 800 results of 9,087 for search 'VidCon~', query time: 4.60s Refine Results
  1. 781
  2. 782
  3. 783

    Key frame extraction algorithm for surveillance videos using an evolutionary approach by Manjusha Rajan, Latha Parameswaran

    Published 2025-01-01
    “…Key Frame Extraction (KFE) algorithms are crucial in video summarization, compression, and offline analysis. …”
    Get full text
    Article
  4. 784
  5. 785

    A video encryption in HEVC entropy coding based on magic square by Bowen XU, Xiaodong WANG, Lei GUO, Jian WANG

    Published 2018-03-01
    Subjects: “…high efficiency video coding…”
    Get full text
    Article
  6. 786

    Local Feature Filtering Method for Dynamic Multiframe Video Sequence Images by Dawei Zhang, Dan Huang

    Published 2022-01-01
    “…To improve the quality of local feature filtering for dynamic multiframe video sequence images, this study is aimed at designing an improved nontexture class noise filtering algorithm based on noise construction denoising algorithm and gray histogram of pixel points, and then designs a texture noise denoising algorithm based on texture smoothing processing and circular gradient values. …”
    Get full text
    Article
  7. 787

    Video Traffic Flow Analysis in Distributed System during Interactive Session by Soumen Kanrar, Niranjan Kumar Mandal

    Published 2016-01-01
    “…Cost effective, smooth multimedia streaming to the remote customer through the distributed “video on demand” architecture is the most challenging research issue over the decade. …”
    Get full text
    Article
  8. 788
  9. 789
  10. 790
  11. 791
  12. 792

    Development of a Video-Test of Emotional Intelligence for Teachers (ViTIED) by María-Pilar Berrios-Martos, Raquel Palomera

    Published 2024-12-01
    “…The test comprises 12 video scenes designed to elicit intra- and interpersonal processes, as well as both positive and negative emotions. …”
    Get full text
    Article
  13. 793
  14. 794

    Federated learning based intelligent edge computing technique for video surveillance by Yu ZHAO, Jie YANG, Miao LIU, Jinlong SUN, Guan GUI

    Published 2020-10-01
    “…With the explosion of global data,centralized cloud computing cannot provide low-latency,high-efficiency video surveillance services.A distributed edge computing model was proposed,which directly processed video data at the edge node to reduce the transmission pressure of the network,eased the computational burden of the central cloud server,and reduced the processing delay of the video surveillance system.Combined with the federated learning algorithm,a lightweight neural network was used,which trained in different scenarios and deployed on edge devices with limited computing power.Experimental results show that,compared with the general neural network model,the detection accuracy of the proposed method is improved by 18%,and the model training time is reduced.…”
    Get full text
    Article
  15. 795

    How Color Properties Can Be Used to Elicit Emotions in Video Games by Erik Geslin, Laurent Jégou, Danny Beaudoin

    Published 2016-01-01
    “…Since the income of the video game industry exceeds that of the film industry, the field of inducting emotions through video games and virtual environments is attracting more attention. …”
    Get full text
    Article
  16. 796

    Effectiveness of Video Self-Modeling on Hope and Daily Activities of Indonesian Youth by Nur'aini Azizah, Peter Dowrick, Tri Lestari

    Published 2023-07-01
    Subjects: “…video self modelling, behavioral intervention, hope…”
    Get full text
    Article
  17. 797
  18. 798
  19. 799

    Neural network and Markov based combination prediction algorithm of video popularity by Xuesen MA, Shuyou CHEN, Xiangdong XU, Zhaokun CHU

    Published 2021-08-01
    “…Caching popular video into user-side in advance improves the user experience and reduces operator costs, which is a common practice in the industry.How to effectively predict the popularity of videos has become a hot issue in the industry.On account of the shortcomings of traditional prediction algorithms such as poor nonlinear mapping ability, low prediction accuracy and weak adaptability, a video popularity prediction algorithm based on a neural network and Markov combined model (Mar-BiLSTM) was proposed.Information dependencies were preserved by constructing bidirectional memory network model (bi-directional long short-term memory, BiLSTM), the prediction accuracy of the model was further improved by using Markov properties while avoiding the increase of the complexity of the model caused by the introduction of external variables.Experimental results show that compared with traditional time series and classic neural network algorithms, the proposed algorithm improves predicting accuracy, effectiveness and reduces the amount of calculation.…”
    Get full text
    Article
  20. 800