Application of Self Organizing Map to Preprocessing Input Vectors for Convolutional Neural Network

被引：1
|
作者：
Dozono, Hiroshi [1 ]
Tanaka, Masafumi [1 ]
机构：
[1] Saga Univ, 1 Honjyo, Saga 8408502, Japan
来源：
ARTIFICIAL NEURAL NETWORKS AND MACHINE LEARNING - ICANN 2019: DEEP LEARNING, PT II | 2019年 / 11728卷
关键词：
Self Organizing Map; Convolutional Neural Network; Data compression;
D O I：
10.1007/978-3-030-30484-3_8
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Recently, the applications of Artificial Intelligence are widely spread in many areas of research. They almost use tailor made classification engine of Deep Learning, and many of such engines uses Convolutional Neural Networks. In this paper, we propose a method for preprocessing the un-structured data to the 2 dimensional data suitable for CNN using Self Organizing Map. The performance is evaluated with the experiments using KDD cup 99 data as input vectors.
引用
收藏
页码：96 / 100
页数：5
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