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Kernel-based classifiers with applications to face detection

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Kernel-based classifiers with applications to face detection

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Saliency-based representations and multi-component classifiers for visual scene recognition

Semi-supervised and unsupervised kernel-based novelty detection with application to remote sensing images

Laplacian Support Vector Analysis for Subspace Discriminative Learning

Scene Recognition with Naive Bayes Non-linear Learning

Sample Distillation for Object Detection and Image Classification

Classification of selectively constrained DNA elements using feature vectors and rule-based classifiers

Efficient Sample Mining for Object Detection

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Score Calibration in Face Recognition

Score Calibration in Face Recognition

Saliency-based representations and multi-component classifiers for visual scene recognition

Semi-supervised and unsupervised kernel-based novelty detection with application to remote sensing images

Scene Recognition with Naive Bayes Non-linear Learning

Laplacian Support Vector Analysis for Subspace Discriminative Learning

Efficient Sample Mining for Object Detection

Score Calibration in Face Recognition

Sample Distillation for Object Detection and Image Classification

Classification of selectively constrained DNA elements using feature vectors and rule-based classifiers

Tractable Approaches to Learning and Planning in High Dimensions

Score Calibration in Face Recognition