C4.5: programs for machine learning
C4.5: programs for machine learning
Efficient and effective querying by image content
Journal of Intelligent Information Systems - Special issue: advances in visual information management systems
Photobook: content-based manipulation of image databases
International Journal of Computer Vision
VisualSEEk: a fully automated content-based image query system
MULTIMEDIA '96 Proceedings of the fourth ACM international conference on Multimedia
Communications of the ACM
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Support vector machine active learning for image retrieval
MULTIMEDIA '01 Proceedings of the ninth ACM international conference on Multimedia
Unsupervised Segmentation of Color-Texture Regions in Images and Video
IEEE Transactions on Pattern Analysis and Machine Intelligence
SIMPLIcity: Semantics-Sensitive Integrated Matching for Picture LIbraries
IEEE Transactions on Pattern Analysis and Machine Intelligence
Ontology-Based Photo Annotation
IEEE Intelligent Systems
Machine Learning
Multi-interval Discretization Methods for Decision Tree Learning
SSPR '98/SPR '98 Proceedings of the Joint IAPR International Workshops on Advances in Pattern Recognition
Decoding Image Semantics Using Composite Region Templates
CBAIVL '98 Proceedings of the IEEE Workshop on Content - Based Access of Image and Video Libraries
NeTra: a toolbox for navigating large image databases
ICIP '97 Proceedings of the 1997 International Conference on Image Processing (ICIP '97) 3-Volume Set-Volume 1 - Volume 1
A Metric for Distributions with Applications to Image Databases
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Simplifying decision trees: A survey
The Knowledge Engineering Review
Hierarchical clustering of WWW image search results using visual, textual and link information
Proceedings of the 12th annual ACM international conference on Multimedia
A bootstrapping framework for annotating and retrieving WWW images
Proceedings of the 12th annual ACM international conference on Multimedia
CVPRW '04 Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 12 - Volume 12
IEEE Transactions on Pattern Analysis and Machine Intelligence
A survey of content-based image retrieval with high-level semantics
Pattern Recognition
Negative Samples Analysis in Relevance Feedback
IEEE Transactions on Knowledge and Data Engineering
Learning in region-based image retrieval
CIVR'03 Proceedings of the 2nd international conference on Image and video retrieval
Region-Based image retrieval with perceptual colors
PCM'04 Proceedings of the 5th Pacific Rim Conference on Advances in Multimedia Information Processing - Volume Part II
IEEE Transactions on Multimedia
Relevance feedback: a power tool for interactive content-based image retrieval
IEEE Transactions on Circuits and Systems for Video Technology
A review on automatic image annotation techniques
Pattern Recognition
Region based color image retrieval using curvelet transform
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part II
Rotation Invariant Curvelet Features for Region Based Image Retrieval
International Journal of Computer Vision
An annotation rule extraction algorithm for image retrieval
Pattern Recognition Letters
Region-based image retrieval using the semantic cluster matrix and adaptive learning
International Journal of Computational Science and Engineering
Automatic image annotation using semantic relevance
Proceedings of the Fifth International Conference on Internet Multimedia Computing and Service
Image retrieval based on high level concept detection and semantic labelling
Intelligent Decision Technologies
Structural image retrieval using automatic image annotation and region based inverted file
Journal of Visual Communication and Image Representation
Neighborhood rough sets based multi-label classification for automatic image annotation
International Journal of Approximate Reasoning
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Semantic-based image retrieval has attracted great interest in recent years. This paper proposes a region-based image retrieval system with high-level semantic learning. The key features of the system are: (1) it supports both query by keyword and query by region of interest. The system segments an image into different regions and extracts low-level features of each region. From these features, high-level concepts are obtained using a proposed decision tree-based learning algorithm named DT-ST. During retrieval, a set of images whose semantic concept matches the query is returned. Experiments on a standard real-world image database confirm that the proposed system significantly improves the retrieval performance, compared with a conventional content-based image retrieval system. (2) The proposed decision tree induction method DT-ST for image semantic learning is different from other decision tree induction algorithms in that it makes use of the semantic templates to discretize continuous-valued region features and avoids the difficult image feature discretization problem. Furthermore, it introduces a hybrid tree simplification method to handle the noise and tree fragmentation problems, thereby improving the classification performance of the tree. Experimental results indicate that DT-ST outperforms two well-established decision tree induction algorithms ID3 and C4.5 in image semantic learning.