视频重复数据删除采用CNN(Conv2d)和SHA-256哈希

Sriraksha Pj, S. Chaudhari, A. R.
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引用次数: 0

摘要

我们都知道,数字数据的产量呈指数级增长。互联网用户通过云服务提供商将视频数据上传到云端。数字视频的成本和大小都是巨大的。因此,对于旨在优化存储数据的成本和大小的技术有很大的需求。本文通过提取视频的全局特征和局部特征,对视频重复数据删除系统进行了全面的概述。在视频重复数据删除过程中,主要采用Conv2d即CNN算法提取视频的局部特征,以及SHA-256等散列算法提取视频的全局特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Video Deduplication using CNN(Conv2d) and SHA-256 hashing
We all know that there is an exponential growth in the production of digital data. The user of the internet approaches the cloud service providers to upload the video data into the cloud. The cost and size of the digital videos is huge. Hence there is great need for techniques which aims at optimizing the cost and size for storing the data. This paper provides a comprehensive overview of video deduplication system by extracting the global and local features of the video. The major techniques employed in the process of video deduplication are Conv2d i.e., CNN algorithm to extract the local features of the video and hashing algorithms like SHA-256 to extract the global features of the video.
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