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Visual Information Retrieval: The State of the Art

Published: 01 July 2016 Publication History

Abstract

Rich visual information is becoming increasingly important in today's Web, as evidenced by the popularity of social networks, the extensive use of video as a medium, and the compelling graphics and visual effects in movies and games. Here, the author examines the process of searching and retrieving images using a visual query--otherwise known as content-based image retrieval (CBIR).

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  • (2023)Using Online Videos as the Basis for Developing Design Guidelines: A Case Study of AR-Based Assembly InstructionsProceedings of the ACM on Human-Computer Interaction10.1145/36264647:ISS(41-63)Online publication date: 31-Oct-2023
  • (2020)Convolutional neural networks for relevance feedback in content based image retrievalMultimedia Tools and Applications10.1007/s11042-020-09292-979:37-38(26995-27021)Online publication date: 21-Jul-2020
  • (2017)Information fusion in content based image retrievalInformation Fusion10.1016/j.inffus.2017.01.00337:C(50-60)Online publication date: 1-Sep-2017
  1. Visual Information Retrieval: The State of the Art

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    Published In

    cover image IT Professional
    IT Professional  Volume 18, Issue 4
    July 2016
    67 pages

    Publisher

    IEEE Educational Activities Department

    United States

    Publication History

    Published: 01 July 2016

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    Cited By

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    • (2023)Using Online Videos as the Basis for Developing Design Guidelines: A Case Study of AR-Based Assembly InstructionsProceedings of the ACM on Human-Computer Interaction10.1145/36264647:ISS(41-63)Online publication date: 31-Oct-2023
    • (2020)Convolutional neural networks for relevance feedback in content based image retrievalMultimedia Tools and Applications10.1007/s11042-020-09292-979:37-38(26995-27021)Online publication date: 21-Jul-2020
    • (2017)Information fusion in content based image retrievalInformation Fusion10.1016/j.inffus.2017.01.00337:C(50-60)Online publication date: 1-Sep-2017

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