Title :
Image classification using neural networks and ontologies
Author :
Breen, Casey ; Khan, Latifur ; Ponnusamy, Arunkumar
Author_Institution :
Dept. of Comput. Sci., Texas Univ., Dallas, TX, USA
Abstract :
The advent of extremely powerful home PC and the growth of the Internet have made the appearance of multimedia documents a common sight in the computer world. In the world of unstructured data composed of images and other media types, classification often comes at the price of countless hours of manual labor. This research aims to present a scalable system capable of examining images and accurately classifying the image based on its visual content. When retrieving images based on a user´s query, the system yields a minimal amount of irrelevant information (high precision) and ensures a maximum amount of relevant information (high recall).
Keywords :
Internet; content-based retrieval; image classification; image retrieval; meta data; multimedia databases; neural nets; relevance feedback; semantic networks; Internet; image classification; image retrieval; multimedia documents; neural networks; ontologies; precision; relevant information; scalable system; user query; visual content; Artificial neural networks; Computer science; Image classification; Image retrieval; Information retrieval; Internet; Multimedia systems; Neural networks; Ontologies; Personal communication networks;
Conference_Titel :
Database and Expert Systems Applications, 2002. Proceedings. 13th International Workshop on
Print_ISBN :
0-7695-1668-8
DOI :
10.1109/DEXA.2002.1045883