Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (3)
  • Open Access

    ARTICLE

    Adaptive Fusion Neural Networks for Sparse-Angle X-Ray 3D Reconstruction

    Shaoyong Hong1, Bo Yang2, Yan Chen2, Hao Quan3, Shan Liu4, Minyi Tang5,*, Jiawei Tian6,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.1, pp. 1091-1112, 2025, DOI:10.32604/cmes.2025.066165 - 31 July 2025

    Abstract 3D medical image reconstruction has significantly enhanced diagnostic accuracy, yet the reliance on densely sampled projection data remains a major limitation in clinical practice. Sparse-angle X-ray imaging, though safer and faster, poses challenges for accurate volumetric reconstruction due to limited spatial information. This study proposes a 3D reconstruction neural network based on adaptive weight fusion (AdapFusionNet) to achieve high-quality 3D medical image reconstruction from sparse-angle X-ray images. To address the issue of spatial inconsistency in multi-angle image reconstruction, an innovative adaptive fusion module was designed to score initial reconstruction results during the inference stage and… More >

  • Open Access

    ARTICLE

    Contrastive Consistency and Attentive Complementarity for Deep Multi-View Subspace Clustering

    Jiao Wang, Bin Wu*, Hongying Zhang

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 143-160, 2024, DOI:10.32604/cmc.2023.046011 - 25 April 2024

    Abstract Deep multi-view subspace clustering (DMVSC) based on self-expression has attracted increasing attention due to its outstanding performance and nonlinear application. However, most existing methods neglect that view-private meaningless information or noise may interfere with the learning of self-expression, which may lead to the degeneration of clustering performance. In this paper, we propose a novel framework of Contrastive Consistency and Attentive Complementarity (CCAC) for DMVsSC. CCAC aligns all the self-expressions of multiple views and fuses them based on their discrimination, so that it can effectively explore consistent and complementary information for achieving precise clustering. Specifically, the More >

  • Open Access

    ARTICLE

    Adaptive Multi-Feature Fusion for Vehicle Micro-Motor Noise Recognition Considering Auditory Perception

    Ting Zhao1, Weiping Ding1, Haibo Huang1, Yudong Wu1,2,*

    Sound & Vibration, Vol.57, pp. 133-153, 2023, DOI:10.32604/sv.2023.044203 - 21 December 2023

    Abstract The deployment of vehicle micro-motors has witnessed an expansion owing to the progression in electrification and intelligent technologies. However, some micro-motors may exhibit design deficiencies, component wear, assembly errors, and other imperfections that may arise during the design or manufacturing phases. Consequently, these micro-motors might generate anomalous noises during their operation, consequently exerting a substantial adverse influence on the overall comfort of drivers and passengers. Automobile micro-motors exhibit a diverse array of structural variations, consequently leading to the manifestation of a multitude of distinctive auditory irregularities. To address the identification of diverse forms of abnormal… More > Graphic Abstract

    Adaptive Multi-Feature Fusion for Vehicle Micro-Motor Noise Recognition Considering Auditory Perception

Displaying 1-10 on page 1 of 3. Per Page