Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (43)
  • Open Access

    ARTICLE

    Detection of Precipitation Cloud over the Tibet Based on the Improved U-Net

    Runzhe Tao1, *, Yonghong Zhang1, Lihua Wang1, Pengyan Cai1, Haowen Tan2

    CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2455-2474, 2020, DOI:10.32604/cmc.2020.011526 - 16 September 2020

    Abstract Aiming at the problem of radar base and ground observation stations on the Tibet is sparsely distributed and cannot achieve large-scale precipitation monitoring. UNet, an advanced machine learning (ML) method, is used to develop a robust and rapid algorithm for precipitating cloud detection based on the new-generation geostationary satellite of FengYun-4A (FY-4A). First, in this algorithm, the real-time multi-band infrared brightness temperature from FY-4A combined with the data of Digital Elevation Model (DEM) has been used as predictor variables for our model. Second, the efficiency of the feature was improved by changing the traditional convolution… More >

  • Open Access

    ARTICLE

    3-Dimensional Bag of Visual Words Framework on Action Recognition

    Shiqi Wang1, Yimin Yang1, *, Ruizhong Wei1, Qingming Jonathan Wu2

    CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1081-1091, 2020, DOI:10.32604/cmc.2020.09648 - 30 April 2020

    Abstract Human motion recognition plays a crucial role in the video analysis framework. However, a given video may contain a variety of noises, such as an unstable background and redundant actions, that are completely different from the key actions. These noises pose a great challenge to human motion recognition. To solve this problem, we propose a new method based on the 3-Dimensional (3D) Bag of Visual Words (BoVW) framework. Our method includes two parts: The first part is the video action feature extractor, which can identify key actions by analyzing action features. In the video action More >

  • Open Access

    ARTICLE

    Few-Shot Learning with Generative Adversarial Networks Based on WOA13 Data

    Xin Li1,2, Yanchun Liang1,2, Minghao Zhao1,2, Chong Wang1,2,3, Yu Jiang1,2,*

    CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1073-1085, 2019, DOI:10.32604/cmc.2019.05929

    Abstract In recent years, extreme weather events accompanying the global warming have occurred frequently, which brought significant impact on national economic and social development. The ocean is an important member of the climate system and plays an important role in the occurrence of climate anomalies. With continuous improvement of sensor technology, we use sensors to acquire the ocean data for the study on resource detection and disaster prevention, etc. However, the data acquired by the sensor is not enough to be used directly by researchers, so we use the Generative Adversarial Network (GAN) to enhance the… More >

Displaying 41-50 on page 5 of 43. Per Page