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Titlebook: Image Analysis and Processing — ICIAP 2015; 18th International C Vittorio Murino,Enrico Puppo Conference proceedings 2015 Springer Nature S

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Transfer Learning Through Greedy Subset Selection on a target task. In particular, we consider the transfer learning setting where one does not have direct access to the source data, but rather employs the source hypotheses trained from them. Building on the literature on the best subset selection problem, we propose an efficient algorithm that se
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A Parzen-Based Distance Between Probability Measures as an Alternative of Summary Statistics in Apprarameters drawn from a prior distribution, and observed data. This comparison process is based on computing a distance between the summary statistics from the simulated data and the observed data. For complex models, it is usually difficult to define a methodology for choosing or constructing the su
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Unsupervised Classification of Raw Full-Waveform Airborne Lidar Data by Self Organizing Maps LIDAR (Light Detection and Ranging) data, without the need of extracting features from them, that is without any preprocessing. The proposed algorithm allows the classification of points into three classes (“grass”, “trees” and “road”) in two subsequent stages. During the first one, all the raw dat
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