Application of Big Digital Media Data Compression Recognition Algorithm in Modern Art Design Training Intelligence

Youquan Liu, Wenhua Huang
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Abstract

Application of big digital media data compression recognition algorithm in modern art design training intelligence is studied in the paper. There is an aggregation effect on the information represented by the same kind of data, and a distancing effect on the information represented by different types of data, which confirms the point of this paper, that is, the essence of classification is to “identify the differences between species and the similarities within the species”, while the data amount is large enough. Further, the big data compression algorithm and cultural image recognition algorithm are designed. MFS is a dedicated file system for virtualized clusters, while neither traditional NTFS nor ext3 are dedicated file systems for virtualized clusters. With these enhanced ideas, the performance of the model is then tested.
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大数字媒体数据压缩识别算法在现代艺术设计训练智能中的应用
研究了大数字媒体数据压缩识别算法在现代艺术设计训练智能中的应用。对同类数据所代表的信息存在聚集效应,对不同类型数据所代表的信息存在距离效应,这印证了本文的观点,即分类的本质是“识别物种之间的差异和物种内部的相似性”,而数据量足够大。设计了大数据压缩算法和文化图像识别算法。MFS是用于虚拟化集群的专用文件系统,而传统NTFS和ext3都不是用于虚拟化集群的专用文件系统。有了这些增强的想法,就可以测试模型的性能。
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