Incremental Self-Organizing Map (iSOM) in Categorization of Visual Objects

被引：0

作者：

Paplinski, Andrew P. ^{[1
]}

机构：

[1] Monash Univ, Clayton, Vic 3800, Australia

来源：

NEURAL INFORMATION PROCESSING, ICONIP 2012, PT II | 2012年 / 7664卷

关键词：

Self-organizing maps; Incremental learning; Radon transform; 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：

We present a modification of the well-known Self-Organizing Map (SOM) in which we incrementally allocate the neuronal nodes to progressively added new stimuli. Our incremental SOM (iSOM) aims at the situation when a stimulus, or percept, is represented by a number of neuronal nodes a typical case in biological situation when the redundancy of representation of data is important. The iSOM is applied to categorization of visual objects using the recently introduced feature vector based on the angular integral of the Radon transform [10].

引用

页码：125 / 132

页数：8

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