We describe an algorithm for automatically learning discriminative components of objects with SVM classifiers. It is based on growing image parts by minimizing theoretical bounds ...
Bernd Heisele, Thomas Serre, Massimiliano Pontil, ...
In this paper, we propose new photo categorization which is suitable for a home photo album. To enhance the categorization, both local and global concepts of the photos are modeled...
Sang-Kyun Kim, Seungji Yang, Kyong Sok Seo, Yong M...
We propose mixtures of hidden Markov models for modelling clickstreams of web surfers. Hence, the page categorization is learned from the data without the need for a (possibly cumb...
The main difficulty in the binary object classification field lays in dealing with a high variability of symbol appearance. Rotation, partial occlusions, elastic deformations, or...
Human categorization research is dominated by work in classification learning. The field may be in danger of equating the classification learning paradigm with the more general ph...
Bradley C. Love, Arthur B. Markman, Takashi Yamauc...