A high performance adaptive image compression system using a generative neural network: DynAmic Neural Network II (DANN II)

Andres Rios, M. Kabuka
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引用次数: 1

Abstract

The system is guaranteed theoretically to compress to any feasible rate, with as low a distortion rate as required. It also exhibits user selectable compression and error rates, ability to compress general data types, and adaptation to the data source. The compression system is based on a novel family of connectionist algorithms and generative algorithms used in conjunction with new artificial neural network models that permit the determination of a quasi-optimal architecture for compressing a given data source.<>
基于生成神经网络的高性能自适应图像压缩系统:动态神经网络II (DANN II)
理论上,该系统可以保证压缩到任何可行的速率,并具有所需的低失真率。它还展示了用户可选择的压缩和错误率、压缩一般数据类型的能力以及对数据源的适应性。压缩系统基于一系列新颖的连接算法和生成算法,结合新的人工神经网络模型,可以确定压缩给定数据源的准最佳架构
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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