We consider a semi-supervised setting for domain adaptation where only unlabeled data is available for the target domain. One way to tackle this problem is to train a generative m...
In this paper we present a multi-scale morphological method for use in texture classification. A connected operator similar to the morphological hat-transform is defined, and two ...
Andrei Jalba, Jos B. T. M. Roerdink, Michael H. F....
A genetic algorithm-based clustering technique, called GA-clustering, is proposed in this article. The searching capability of genetic algorithms is exploited in order to search f...
Abstract. To solve problems that require far more memory than a single machine can supply, data can be swapped to disk in some manner, it can be compressed, and/or the memory of mu...
We introduce a method for unsupervised clustering of images of 3D objects. Our method examines the space of all images and partitions the images into sets that form smooth and par...