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Latent semantic fusion model for image retrieval and annotation

Published: 06 November 2007 Publication History

Abstract

This paper studies the effect of Latent Semantic Analysis (LSA) on two different tasks: multimedia document retrieval (MDR) and automatic image annotation (AIA). The contributions of this paper are twofold. First, to the best of our knowledge, this work is the first study of the influence of LSA on the retrieval of a significant number of multimedia documents (i.e. collection of 20000 tourist images). Second, it shows how different image representations (region-based and keypoint-based) can be combined by LSA to improve automatic image annotation. The document collections used for these experiments are the Corel photo collection and ImageCLEF 2006 collection.

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    cover image ACM Conferences
    CIKM '07: Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
    November 2007
    1048 pages
    ISBN:9781595938039
    DOI:10.1145/1321440
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 06 November 2007

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    Author Tags

    1. automatic annotation
    2. image indexing and retrieval
    3. latent semantic indexing
    4. multimedia fusion

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    • (2022)Multi-Modal Graph Learning for Disease PredictionIEEE Transactions on Medical Imaging10.1109/TMI.2022.315926441:9(2207-2216)Online publication date: Sep-2022
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