The nature of statistical learning theory
The nature of statistical learning theory
Experiments with a featureless approach to pattern recognition
Pattern Recognition Letters - special issue on pattern recognition in practice V
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Performance evaluation in content-based image retrieval: overview and proposals
Pattern Recognition Letters - Special issue on image/video indexing and retrieval
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Supporting Ranked Boolean Similarity Queries in MARS
IEEE Transactions on Knowledge and Data Engineering
Dissimilarity representations allow for building good classifiers
Pattern Recognition Letters
Machine Learning
Estimating a Kernel Fisher Discriminant in the Presence of Label Noise
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Partially Supervised Classification of Text Documents
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
A decision-theoretic generalization of on-line learning and an application to boosting
EuroCOLT '95 Proceedings of the Second European Conference on Computational Learning Theory
PEBL: positive example based learning for Web page classification using SVM
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Building Text Classifiers Using Positive and Unlabeled Examples
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
International Journal of Computer Vision - Special Issue on Content-Based Image Retrieval
Combining Pattern Classifiers: Methods and Algorithms
Combining Pattern Classifiers: Methods and Algorithms
A Survey of Outlier Detection Methodologies
Artificial Intelligence Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
Introduction to Information Retrieval
Introduction to Information Retrieval
Design of Multimodal Dissimilarity Spaces for Retrieval of Video Documents
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning to classify texts using positive and unlabeled data
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
A comparison of score, rank and probability-based fusion methods for video shot retrieval
CIVR'05 Proceedings of the 4th international conference on Image and Video Retrieval
Interactive Search by Direct Manipulation of Dissimilarity Space
IEEE Transactions on Multimedia
Retrieval of images from artistic repositories using a decision fusion framework
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
IEEE Transactions on Circuits and Systems for Video Technology
Learning a semantic space from user's relevance feedback for image retrieval
IEEE Transactions on Circuits and Systems for Video Technology
Image similarity: from syntax to weak semantics
Multimedia Tools and Applications
Image Dimensionality Reduction Based on the Intrinsic Dimension and Parallel Genetic Algorithm
International Journal of Cognitive Informatics and Natural Intelligence
Multifeature analysis and semantic context learning for image classification
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Robust network traffic identification with unknown applications
Proceedings of the 8th ACM SIGSAC symposium on Information, computer and communications security
Robust image retrieval with hidden classes
Computer Vision and Image Understanding
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Conventional content-based image retrieval (CBIR) schemes employing relevance feedback may suffer from some problems in the practical applications. First, most ordinary users would like to complete their search in a single interaction especially on the web. Second, it is time consuming and difficult to label a lot of negative examples with sufficient variety. Third, ordinary users may introduce some noisy examples into the query. This correspondence explores solutions to a new issue that image retrieval using unclean positive examples. In the proposed scheme, multiple feature distances are combined to obtain image similarity using classification technology. To handle the noisy positive examples, a new two-step strategy is proposed by incorporating the methods of data cleaning and noise tolerant classifier. The extensive experiments carried out on two different real image collections validate the effectiveness of the proposed scheme.