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This article targets the problem of vehicle classification using laser scanner profiles, which is usually found as a component of electronic tolling systems. Laser scanners obtain a 3D measurement of the vehicle surface. Previous approaches have extracted high-level features (such as width, height, length and other measurements) from the scanner profiles, or have taken the raw profiles for further...
We address the problem of large-scale topic classification of web pages based on the minimal text available in the URLs. This problem is challenging because of the sparsity of feature vectors that are derived from the URL text, and the typical asymmetry between the cardinality of train and test sets due to non-availability of sufficient sets of annotated URLs for training and very large test sets...
Handling large amounts of data, such as large image databases, requires the use of approximate nearest neighbor search techniques. Recently, Hamming embedding methods such as spectral hashing have addressed the problem of obtaining compact binary codes optimizing the trade-off between the memory usage and the probability of retrieving the true nearest neighbors. In this paper, we formulate the problem...
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