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Multiple classifier combination methods can be considered some of the most robust and accurate learning approaches. The fields of multiple classifier systems and ensemble learning developed various procedures to train a set of learning machines and combine their outputs. Such methods have been successfully applied to a wide range of real problems, and are often, but not exclusively, used to improve...
This paper presents some more advanced topics in image processing and computer vision, such as Principal Components Analysis, Matching Techniques, Machine Learning Techniques, Tracking and Optical Flow and Parallel Computer Vision using CUDA. These concepts will be presented using the open CV library, which is a free computer vision library for C/C++ programmers available for Windows, Linux Mac OS...
Face recognition is a multidisciplinary field that involves subjects in neuroscience, computer science and statistical learning. Some recent research in neuroscience has indicated that the ability of our memory relies on the capability of orthogonalizing (pattern separation) and completing (pattern prototyping) partial patterns in order to encode, store and recall information. From a computational...
Computational photography tries to expand the concept of traditional photography (a static two dimensional projection of a scene) using state-of-the-art technology. While this can be achieved by combining information from multiple conventional pictures, a more interesting challenge consists in encoding and recovering additional information from one (or more) image(s). Since a photograph results from...
Adessowiki is a collaborative environment for teaching and research in image processing. Adessowiki is composed of a collection of collaborative web pages in the form of a wiki. The articles of this wiki can embed programming code that will be executed on the server when the page is rendered, incorporating the results as figures, texts and tables on the document. The integrated collaborative environment...
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