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  • Open Access

    ARTICLE

    Guided-YNet: Saliency Feature-Guided Interactive Feature Enhancement Lung Tumor Segmentation Network

    Tao Zhou1,3, Yunfeng Pan1,3,*, Huiling Lu2, Pei Dang1,3, Yujie Guo1,3, Yaxing Wang1,3

    CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4813-4832, 2024, DOI:10.32604/cmc.2024.054685 - 12 September 2024

    Abstract Multimodal lung tumor medical images can provide anatomical and functional information for the same lesion. Such as Positron Emission Computed Tomography (PET), Computed Tomography (CT), and PET-CT. How to utilize the lesion anatomical and functional information effectively and improve the network segmentation performance are key questions. To solve the problem, the Saliency Feature-Guided Interactive Feature Enhancement Lung Tumor Segmentation Network (Guide-YNet) is proposed in this paper. Firstly, a double-encoder single-decoder U-Net is used as the backbone in this model, a single-coder single-decoder U-Net is used to generate the saliency guided feature using PET image and… More >

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  • Open Access

    ARTICLE

    Identification of a Printed Anti-Counterfeiting Code Based on Feature Guidance Double Pool Attention Networks

    Changhui You1,2, Hong Zheng1,2,*, Zhongyuan Guo2, Tianyu Wang2, Jianping Ju3, Xi Li3

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3431-3452, 2023, DOI:10.32604/cmc.2023.035897 - 31 March 2023

    Abstract The authenticity identification of anti-counterfeiting codes based on mobile phone platforms is affected by lighting environment, photographing habits, camera resolution and other factors, resulting in poor collection quality of anti-counterfeiting codes and weak differentiation of anti-counterfeiting codes for high-quality counterfeits. Developing an anti-counterfeiting code authentication algorithm based on mobile phones is of great commercial value. Although the existing algorithms developed based on special equipment can effectively identify forged anti-counterfeiting codes, the anti-counterfeiting code identification scheme based on mobile phones is still in its infancy. To address the small differences in texture features, low response speed… More >

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