Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Support vector machine active learning for image retrieval
MULTIMEDIA '01 Proceedings of the ninth ACM international conference on Multimedia
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Image retrieval: Ideas, influences, and trends of the new age
ACM Computing Surveys (CSUR)
SVM-based active feedback in image retrieval using clustering and unlabeled data
Pattern Recognition
Performance evaluation of relevance feedback methods
CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
IEEE Transactions on Image Processing
Biased discriminant euclidean embedding for content-based image retrieval
IEEE Transactions on Image Processing
Image retrieval based on incremental subspace learning
Pattern Recognition
Asymmetric semi-supervised boosting for SVM active learning in CBIR
Proceedings of the ACM International Conference on Image and Video Retrieval
Bregman Divergence-Based Regularization for Transfer Subspace Learning
IEEE Transactions on Knowledge and Data Engineering
Local-feature-based image retrieval with weighted relevance feedback
International Journal of Business Intelligence and Data Mining
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ACM Transactions on Intelligent Systems and Technology (TIST)
A Lazy Processing Approach to User Relevance Feedback for Content-Based Image Retrieval
ISM '10 Proceedings of the 2010 IEEE International Symposium on Multimedia
Expert Systems with Applications: An International Journal
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part III
Image retrieval systems based on compact shape descriptor and relevance feedback information
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IEEE Transactions on Audio, Speech, and Language Processing
A Stochastic Approach to Image Retrieval Using Relevance Feedback and Particle Swarm Optimization
IEEE Transactions on Multimedia
IEEE Transactions on Image Processing
Active Learning Methods for Interactive Image Retrieval
IEEE Transactions on Image Processing
Semantic Subspace Projection and Its Applications in Image Retrieval
IEEE Transactions on Circuits and Systems for Video Technology
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A Survey on Visual Content-Based Video Indexing and Retrieval
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Beyond cross-domain learning: Multiple-domain nonnegative matrix factorization
Engineering Applications of Artificial Intelligence
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Relevance feedback (RF) is an effective approach to bridge the gap between low-level visual features and high-level semantic meanings in content-based image retrieval (CBIR). The active support vector machine (SVM) based RFs have been popular because they can outperform many other classifiers when the size of the training set is small, but they are often very complex and some unsatisfactory relevance of results occur frequently. To overcome the above limitations, an active SVM-based RF using multiple classifiers ensemble and features reweighting is proposed in this paper. Firstly, we select the most informative images by using active learning method for user to label, and quickly learn a boundary that separates the images that satisfy the user's query concept from the rest of the dataset. Secondly, the feature space is modified dynamically by appropriately weighting the descriptive features according to a set of statistical characteristics. Then, a set of moderate accurate one-class SVM classifiers are trained separately by using different new sub-features vectors. Finally, we compute the weight vector of component SVM classifiers dynamically by using the parameters for positive and negative samples, and combine the results of the component classifiers to form an output code as a hypothesized solution to the overall image retrieval problem. Extensive simulations on large databases show that the proposed algorithm is significantly more effective than the state-of-the-art approaches.