Abstract. In this paper we elaborate on a kernel extension to tensorbased data analysis. The proposed ideas find applications in supervised learning problems where input data have ...
Marco Signoretto, Lieven De Lathauwer, Johan A. K....
Large-scale digitization projects aimed at periodicals often have as input streams of completely unlabeled document images. In such situations, the results produced by the automat...
Iuliu Vasile Konya, Christoph Seibert, Sebastian G...
— Selective data return leverages onboard data analysis to allocate limited bandwidth resources during remote exploration. Here we present an adaptive method to subsample image s...
In this paper, we present the results of a project that seeks to transform low-level features to a higher level of meaning. This project concerns a technique, latent semantic anal...
In this paper we explore the effectiveness of three clustering methods used to perform word image indexing. The three methods are: the Self-Organazing Map (SOM), the Growing Hiera...