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Distributed image file system based on human cognition

机译:基于人类认知的分布式图像文件系统

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Big Data era is characterized by the explosive increase of image files on the Internet, massive image files bring great challenges to storage. It is required not only the storage efficiency of massive image files but also the accuracy and robustness of massive image file management and retrieval. To meet these requirements, distributed image file storage system based on cognition is proposed. According to the human brain function, humans can correlate image files with thousands of distinct object and action categories and sorted store these files. Thus we proposed to sorted store image files according to different visual categories based on human cognition. The experimental results demonstrate that the proposed distributed image file system (DIFS) based on cognition performs better than Hadoop Distributed File System (HDFS).
机译:大数据时代的特点是互联网上图像文件的爆炸性增加,巨大的图像文件为存储带来了极大的挑战。 不仅需要大量图像文件的存储效率,还需要大量图像文件管理和检索的准确性和稳健性。 为了满足这些要求,提出了基于认知的分布式图像文件存储系统。 根据人类脑功能,人类可以将图像文件与数千个不同的对象和行动类别相关联,并排序存储这些文件。 因此,我们建议根据基于人类认知的不同视觉类别对商店图像文件进行排序。 实验结果表明,基于认知的提议的分布式图像文件系统(DIFS)比Hadoop分布式文件系统(HDFS)更好地执行。

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