Adaptive Image Replica Detection based on Support Vector Classifiers
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Computerized analysis of digital pathology images offers the potential of improving clinical care (e.g. automated diagnosis) and catalyzing research (e.g. discovering disease subtypes). There are two key challenges thwarting computerized analysis of digita ...
In recent years, there has been a growing interest in developing countermeasures against non zero-effort attacks for speaker verification systems. Until now, the focus has been on logical access attacks, where the spoofed samples are injected into the syst ...
Scarce work has been done in the analysis of the composition of conserved non-coding elements (CNEs) that are identified by comparisons of two or more genomes and are found to exist in all metazoan genomes. Here we present the analysis of CNEs with a metho ...
Classifiers based on sparse representations have recently been shown to provide excellent results in many visual recognition and classification tasks. However, the high cost of computing sparse representations at test time is a major obstacle that limits t ...
State-of-the-art image and action classification systems often employ vocabulary-based representations. The classification accuracy achieved with such vocabulary-based representations depends significantly on the chosen histogram-distance. In particular, w ...
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Inverse solution allows to estimate sources that generate a given scalp EEG topography. Recently, it has been used in Brain Computer Interfaces (BCIs) to extract robust features based on the hypothesis that projection onto the source space (high dimensiona ...
In this work a new method for automatic image classification is proposed. It relies on a compact representation of images using sets of sparse binary features. This work first evaluates the Fast Retina Keypoint binary descriptor and proposes imp ...
The main challenge of new information technologies is to retrieve intelligible information from the large volume of digital data gathered every day. Among the variety of existing data sources, the satellites continuously observing the surface of the Earth ...
Fisher kernels combine the powers of discriminative and generative classifiers by mapping the variable-length sequences to a new fixed length feature space, called the Fisher score space. The mapping is based on a single generative model and the classifier ...
A failure detector is a fundamental abstraction in distributed computing. This paper surveys this abstraction through two dimensions. First we study failure detectors as building blocks to simplify the design of reliable distributed algorithms. In particul ...