Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
A comparison of wavelet transform features for texture image annotation
ICIP '95 Proceedings of the 1995 International Conference on Image Processing (Vol.2)-Volume 2 - Volume 2
Semi-Supervised Learning on Riemannian Manifolds
Machine Learning
Mean version space: a new active learning method for content-based image retrieval
Proceedings of the 6th ACM SIGMM international workshop on Multimedia information retrieval
Enhancing relevance feedback in image retrieval using unlabeled data
ACM Transactions on Information Systems (TOIS)
Relevance Feedback and Category Search in Image Databases
ICMCS '99 Proceedings of the IEEE International Conference on Multimedia Computing and Systems - Volume 2
Random sampling based SVM for relevance feedback image retrieval
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Bootstrapping SVM active learning by incorporating unlabelled images for image retrieval
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
IEEE Transactions on Multimedia
IEEE Transactions on Image Processing
CLUE: cluster-based retrieval of images by unsupervised learning
IEEE Transactions on Image Processing
Relevance feedback: a power tool for interactive content-based image retrieval
IEEE Transactions on Circuits and Systems for Video Technology
An SVM-based machine learning method for accurate internet traffic classification
Information Systems Frontiers
Relevance feedback based on genetic programming for image retrieval
Pattern Recognition Letters
A relevance feedback-based learner for image retrieval using SIFT descriptors
International Journal of Computational Vision and Robotics
Remote sensing image segmentation by active queries
Pattern Recognition
A cluster-assumption based batch mode active learning technique
Pattern Recognition Letters
Inconsistency-based active learning for support vector machines
Pattern Recognition
Robust twin support vector machine for pattern classification
Pattern Recognition
Active SVM-based relevance feedback using multiple classifiers ensemble and features reweighting
Engineering Applications of Artificial Intelligence
Structural twin support vector machine for classification
Knowledge-Based Systems
Combining active learning and semi-supervised learning to construct SVM classifier
Knowledge-Based Systems
Using robust dispersion estimation in support vector machines
Pattern Recognition
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In content-based image retrieval, relevance feedback is studied extensively to narrow the gap between low-level image feature and high-level semantic concept. However, most methods are challenged by small sample size problem since users are usually not so patient to label a large number of training instances in the relevance feedback round. In this paper, this problem is solved by two strategies: (1) designing a new active selection criterion to select images for user's feedback. It takes both the informative and the representative measures into consideration, thus the diversities between these images are increased while their informative powers are kept. With this new criterion, more information gain can be obtained from the feedback images; and (2) incorporating unlabeled images within the co-training framework. Unlabeled data partially alleviates the training data scarcity problem, thus improves the efficiency of support vector machine (SVM) active learning. Systematic experimental results verify the superiority of our method over existing active learning methods.