Application of Spiking Neural Networks to Fashion Classification

被引：0

作者：

Opielka, Piotr ^{[1
]}

Starczewski, Janusz T. ^{[1
]}

Wrobel, Michal ^{[1
]}

Nieszporek, Katarzyna ^{[1
]}

Marchlewska, Alina ^{[2
,3
]}

机构：

[1] Czestochowa Tech Univ, Inst Computat Intelligence, Czestochowa, Poland

[2] Univ Social Sci, Informat Technol Inst, Lodz, Poland

[3] Clark Univ, Worcester, MA 01610 USA

来源：

ARTIFICIAL INTELLIGENCEAND SOFT COMPUTING, PT I | 2019年 / 11508卷

关键词：

D O I：

10.1007/978-3-030-20912-4_17

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, a model of spiking neural networks is studied. Such networks are commonly called as the third generation of artificial neural networks. The main difference between them and previous generation networks is that they are based on spiking neurons. This approach leads us to the need of using specific ways of coding inputs and outputs as well as original methods of learning. The paper considers evaluation of such a network with a Fashion-MNIST dataset that contains labeled images. The results of this experiment and its conclusion are also described in the paper.

引用

页码：172 / 180

页数：9

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