Submit

Login Login

Register Register

Home / Advanced Search
News & Announcements

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
Show export options
  • Articles
  • Online
Search Results (2)

  • Open Access

    ARTICLE

    Rolling Bearing Fault Diagnosis Based on 1D Convolutional Neural Network and Kolmogorov–Arnold Network for Industrial Internet

    Huyong Yan1, Huidong Zhou2,*, Jian Zheng1, Zhaozhe Zhou1

    CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 4659-4677, 2025, DOI:10.32604/cmc.2025.062807 - 19 May 2025

    Abstract As smart manufacturing and Industry 4.0 continue to evolve, fault diagnosis of mechanical equipment has become crucial for ensuring production safety and optimizing equipment utilization. To address the challenge of cross-domain adaptation in intelligent diagnostic models under varying operational conditions, this paper introduces the CNN-1D-KAN model, which combines a 1D Convolutional Neural Network (1D-CNN) with a Kolmogorov–Arnold Network (KAN). The novelty of this approach lies in replacing the traditional 1D-CNN’s final fully connected layer with a KANLinear layer, leveraging KAN’s advanced nonlinear processing and function approximation capabilities while maintaining the simplicity of linear transformations. Experimental… More >

    View

    1823

    Download

    806

  • Open Access

    ARTICLE

    Enhancing Human Action Recognition with Adaptive Hybrid Deep Attentive Networks and Archerfish Optimization

    Ahmad Yahiya Ahmad Bani Ahmad1, Jafar Alzubi2, Sophers James3, Vincent Omollo Nyangaresi4,5,*, Chanthirasekaran Kutralakani6, Anguraju Krishnan7

    CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4791-4812, 2024, DOI:10.32604/cmc.2024.052771 - 12 September 2024

    Abstract In recent years, wearable devices-based Human Activity Recognition (HAR) models have received significant attention. Previously developed HAR models use hand-crafted features to recognize human activities, leading to the extraction of basic features. The images captured by wearable sensors contain advanced features, allowing them to be analyzed by deep learning algorithms to enhance the detection and recognition of human actions. Poor lighting and limited sensor capabilities can impact data quality, making the recognition of human actions a challenging task. The unimodal-based HAR approaches are not suitable in a real-time environment. Therefore, an updated HAR model is… More >

    View

    1415

    Download

    642

Displaying 1-10 on page 1 of 2. Per Page  

Contact Us

Copyright© 2026 Tech Science Press
© 1997-2026 TSP (Henderson, USA) unless otherwise stated