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  • Open Access


    Refined Sparse Representation Based Similar Category Image Retrieval

    Xin Wang, Zhilin Zhu, Zhen Hua*

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.2, pp. 893-908, 2023, DOI:10.32604/cmes.2022.021287

    Abstract Given one specific image, it would be quite significant if humanity could simply retrieve all those pictures that fall into a similar category of images. However, traditional methods are inclined to achieve high-quality retrieval by utilizing adequate learning instances, ignoring the extraction of the image’s essential information which leads to difficulty in the retrieval of similar category images just using one reference image. Aiming to solve this problem above, we proposed in this paper one refined sparse representation based similar category image retrieval model. On the one hand, saliency detection and multi-level decomposition could contribute to taking salient and spatial… More >

  • Open Access


    Comprehensive Information Security Evaluation Model Based on Multi-Level Decomposition Feedback for IoT

    Jinxin Zuo1, 3, Yueming Lu1, 3, *, Hui Gao2, 3, Ruohan Cao2, 3, Ziyv Guo2, 3, Jim Feng4

    CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 683-704, 2020, DOI:10.32604/cmc.2020.010793

    Abstract The development of the Internet of Things (IoT) calls for a comprehensive information security evaluation framework to quantitatively measure the safety score and risk (S&R) value of the network urgently. In this paper, we summarize the architecture and vulnerability in IoT and propose a comprehensive information security evaluation model based on multi-level decomposition feedback. The evaluation model provides an idea for information security evaluation of IoT and guides the security decision maker for dynamic protection. Firstly, we establish an overall evaluation indicator system that includes four primary indicators of threat information, asset, vulnerability, and management, respectively. It also includes eleven… More >

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