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Ranking objects is an essential problem in recommendation systems. Since comparing two objects is the simplest type of queries in order to measure the relevance of objects, the problem of aggregating pair wise comparisons to obtain a global ranking has been widely studied. In order to learn a ranking model, a training set of queries as well as their correct labels are supplied and a machine learning...
We propose a new spectral-spatial method for hyperspectral image classification based on a graph cut. The classification task is formulated as an energy minimization problem on the graph of image pixels, and is solved by using the graph-cut α-expansion approach. The energy to optimize is computed as a sum of data and interaction energy terms, respectively. The data energy term is computed using the...
We implement two popular WiFi, fingerprinting based indoor tracking mechanisms, namely the k-nearest neighbours and probabilistic positioning methods. Both mechanisms are evaluated in the context of an indoor position-tracking tablet application, following an investigation to determine optimal working parameters. Our results indicate that even after significant optimisation, both fingerprinting algorithms...
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