SOFT CATEGORIZATION AND ANNOTATION OF IMAGES WITH RADIAL BASIS FUNCTION NETWORKS

被引：0

作者：

Carullo, Moreno ^{[1
]}

Binaghi, Elisabetta ^{[1
]}

Gallo, Ignazio ^{[1
]}

机构：

[1] Univ Insubria, Varese, Italy

来源：

VISAPP 2009: PROCEEDINGS OF THE FOURTH INTERNATIONAL CONFERENCE ON COMPUTER VISION THEORY AND APPLICATIONS, VOL 2 | 2009年

关键词：

Content-based image retrieval; Image categorization; Image annotation; Soft classification; Neural networks; CLASSIFICATION; ACCURACY;

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 work focuses on fast approaches for image retrieval and classification by employing simple features to build image signatures. For this purpose a neural model for soft classification and automatic image annotation is proposed. The salient aspects of this solution are: a) the employment of a Radial Basis Function Network built on top of an image retrieval distance metric b) a soft learning strategy for annotation handling. Experiments have been conducted on a subset of the Corel image dataset for evaluation and comparative analysis.

引用

页码：309 / 314

页数：6

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