Classification of dog barks: a machine learning approach
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Machine Learning is a modern and actively developing field of computer science, devoted to extracting and estimating dependencies from empirical data. It combines such fields as statistics, optimization theory and artificial intelligence. In practical task ...
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Multiple kernel learning (MKL) aims at simultaneously learning a kernel and the associated predictor in supervised learning settings. For the support vector machine, an efficient and general multiple kernel learning algorithm, based on semi-infinite linear ...
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Feature selection is a machine learning technique that has many interesting applications in the area of brain- computer interfaces (BCIs). Here we show how automatic relevance determination (ARD), which is a Bayesian feature selection technique, can be app ...
Feature extraction based on different types of signal filters has received a lot of attention in the context of face recognition. It generally results into extremely high dimensional feature vectors, and sampling of the coefficients is required to reduce t ...
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The recognition of events in multimedia data is a challenging area of research. The growth in the amount of multimedia data being produced and stored increases the need for systems capable of automatically analysing this data. This analysis can aid in effi ...
A new learning strategy for object detection is presented. The proposed scheme forgoes the need to train a collection of detectors dedicated to homogeneous families of poses, and instead learns a single classifier that has the inherent ability to deform ba ...
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