Content-Based Image Retrieval Using Multiple Representations

Karin Kailing; Hans‐Peter Kriegel; Stefan Schönauer

doi:10.1007/978-3-540-30133-2_130

ScienceGate Book Chapters

BOOK-CHAPTER

Content-Based Image Retrieval Using Multiple Representations

Karin Kailing Hans‐Peter Kriegel Stefan Schönauer

Year: 2004 Lecture notes in computer science Pages: 982-988 Publisher: Springer Science+Business Media

DOI: 10.1007/978-3-540-30133-2_130

Get Full-Text PDF Get Analytical Report

Keywords:

Computer science Image retrieval Cluster analysis Representation (politics) Content-based image retrieval Simple (philosophy) Artificial intelligence Graph Image (mathematics) Information retrieval Pattern recognition (psychology) Tree structure Visual Word Tree (set theory) Data mining Data structure Theoretical computer science Mathematics

Metrics

Cited By

0.59

FWCI (Field Weighted Citation Impact)

Refs

0.67

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Image Retrieval and Classification Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Advanced Image and Video Retrieval Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Video Analysis and Summarization

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Content-Based Image Retrieval Using Multiple Representations

Metrics

Citation History

Topics

Related Documents

Ar .obust content-based image retrieval system using multiple features representations

Content-Based Image Retrieval Using Multiple Features

Using multiple examples for content-based image retrieval

Content-based Image Retrieval using Multiple Shape Descriptors

Multiple representations, similarity matching, and results fusion for content-based image retrieval