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    戚金清

    • 副教授       硕士生导师
    • 性别:男
    • 毕业院校:东京工业大学
    • 学位:博士
    • 所在单位:信息与通信工程学院
    • 学科:通信与信息系统. 信号与信息处理
    • 电子邮箱:jinqing@dlut.edu.cn

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    Restricted Boltzmann Machine for Saliency Detection

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    论文类型:会议论文

    发表时间:2015-09-22

    收录刊物:EI、CPCI-S、Scopus

    页面范围:19-24

    关键字:Saliency; Restricted Boltzmann Machine; Optimization

    摘要:Saliency detection is the task of locating informative regions and objects in an image, which is a challenging task in computer vision. In this paper, we introduce an effective generative model using the Restricted Boltzmann Machine (RBM) for salient object detection. First, RBM is adopted to model the global shape of input images based on regional features. Second, an effective optimization method is used to refine the initial shape map with local relations and detailed information. Experimental results on benchmark datasets demonstrate that the proposed RBM model for saliency detection works more effectively than some existing state-of-the-art algorithms.