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  1. Journal of Computer Science and Technology
  2. Journal of Computer Science and Technology : Volume 27
  3. Journal of Computer Science and Technology : Volume 27, Issue 1, January 2012
  4. HBIR: Hypercube-Based Image Retrieval
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Journal of Computer Science and Technology : Volume 32
Journal of Computer Science and Technology : Volume 31
Journal of Computer Science and Technology : Volume 30
Journal of Computer Science and Technology : Volume 29
Journal of Computer Science and Technology : Volume 28
Journal of Computer Science and Technology : Volume 27
Journal of Computer Science and Technology : Volume 27, Issue 6, November 2012
Journal of Computer Science and Technology : Volume 27, Issue 5, September 2012
Journal of Computer Science and Technology : Volume 27, Issue 4, July 2012
Journal of Computer Science and Technology : Volume 27, Issue 2, March 2012
Journal of Computer Science and Technology : Volume 27, Issue 3, January 2012
Journal of Computer Science and Technology : Volume 27, Issue 1, January 2012
Dynamic Uncertain Causality Graph for Knowledge Representation and Reasoning: Discrete DAG Cases
Publishing Set-Valued Data Against Realistic Adversaries
Integrating Standard Dependency Schemes in QCSP Solvers
Providing Source Code Level Portability Between CPU and GPU with MapCG
A Hybrid Circular Queue Method for Iterative Stencil Computations on GPUs
Effcient Handling of Lock Hand-off in DSM Multiprocessors with Buffering Coherence Controllers
Mercury: Combining Performance with Dependability Using Self-Virtualization
Optimal Checkpoint Placement on Real-Time Tasks with Harmonic Periods
Cell Mapping for Nanohybrid Circuit Architecture Using Genetic Algorithm
Fast Multi-Operator Image Resizing and Evaluation
Real-Time Simulation of Aeolian Sand Movement and Sand Ripple Evolution: A Method Based on the Physics of Blown Sand
HBIR: Hypercube-Based Image Retrieval
Feature-Preserving Mesh Denoising via Anisotropic Surface Fitting
New Explorations on Cannon’s Contributions and Generalized Solutions for Uniform Linear Motion Blur Identification
Extended Approach to Water Flow Algorithm for Text Line Segmentation
Related Axis: The Extension to XPath Towards Effective XML Search
A Reprocessing Model for Complete Execution of RFID Access Operations on Tag Memory
Journal of Computer Science and Technology : Volume 26
Journal of Computer Science and Technology : Volume 25
Journal of Computer Science and Technology : Volume 24
Journal of Computer Science and Technology : Volume 23
Journal of Computer Science and Technology : Volume 22
Journal of Computer Science and Technology : Volume 21
Journal of Computer Science and Technology : Volume 20
Journal of Computer Science and Technology : Volume 19
Journal of Computer Science and Technology : Volume 18
Journal of Computer Science and Technology : Volume 17
Journal of Computer Science and Technology : Volume 16
Journal of Computer Science and Technology : Volume 15
Journal of Computer Science and Technology : Volume 14
Journal of Computer Science and Technology : Volume 13
Journal of Computer Science and Technology : Volume 12

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HBIR: Hypercube-Based Image Retrieval

Content Provider Springer Nature Link
Author Ajorloo, Hossein Lakdashti, Abolfazl
Copyright Year 2012
Abstract In this paper, we propose a mapping from low level feature space to the semantic space drawn by the users through relevance feedback to enhance the performance of current content based image retrieval (CBIR) systems. The proposed approach makes a rule base for its inference and configures it using the feedbacks gathered from users during the life cycle of the system. Each rule makes a hypercube (HC) in the feature space corresponding to a semantic concept in the semantic space. Both short and long term strategies are taken to improve the accuracy of the system in response to each feedback of the user and gradually bridge the semantic gap. A scoring paradigm is designed to determine the effective rules and suppress the inefficient ones. For improving the response time, an HC merging approach and, for reducing the conflicts, an HC splitting method is designed. Our experiments on a set of 11 000 images from the Corel database show that the proposed approach can better describe the semantic content of images for image retrieval with respect to some existing approaches reported recently in the literature. Moreover, our approach can be better trained and is not saturated in long time, i.e., any feedback improves the precision and recall of the system. Another strength of our method is its ability to address the dynamic nature of the image database such that it can follow the changes occurred instantaneously and permanently by adding and dropping images.
Starting Page 147
Ending Page 162
Page Count 16
File Format PDF
ISSN 10009000
Journal Journal of Computer Science and Technology
Volume Number 27
Issue Number 1
e-ISSN 18604749
Language English
Publisher Springer US
Publisher Date 2012-01-09
Publisher Place Boston
Access Restriction One Nation One Subscription (ONOS)
Subject Keyword image retrieval relevance feedback rule base hypercube (HC) Theory of Computation Artificial Intelligence (incl. Robotics) Computer Science Information Systems Applications (incl. Internet) Data Structures, Cryptology and Information Theory Software Engineering
Content Type Text
Resource Type Article
Subject Theoretical Computer Science Computational Theory and Mathematics Computer Science Applications Software Hardware and Architecture
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