GA-based Fractal and Neuroevolution Compressions

被引：0

作者：

Tkachuk, Vladislav ^{[1
]}

Koreneva, Maria ^{[1
]}

Afanasyev, Ilya ^{[2
]}

Rivera, Victor ^{[3
]}

Mazzara, Manuel ^{[3
]}

机构：

[1] Innopolis Univ, Innopolis, Russia

[2] Innopolis Univ, Inst Robot, Innopolis, Russia

[3] Innopolis Univ, Inst Technol & Software Dev, Innopolis, Russia

来源：

2018 9TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS (IS) | 2018年

关键词：

image compression; genetic algorithm; fractal compression; adaptive neural network; Gabor's filter; IMAGE COMPRESSION; LOSSLESS COMPRESSION; NEURAL-NETWORK;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents a compression methodology using genetic algorithms and web-services to test it. The algorithm combines two well-known algorithms of fractal and neural network compressions, making some improvements in their implementation. Thus, in fractal compression we increased speed of compression by a genetic search and in neural networks we used neuroevolution approach for adaptive neural networks. This type of network uses previously processed data to increase the compression rate. In general case, our algorithm outperformed JPEG by 12%.

引用

页码：260 / 266

页数：7

共 36 条

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