We present a discriminative part-based approach for human action recognition from video sequences using motion features. Our model is based on the recently proposed hidden conditi...
Unsupervised learning algorithms have been derived for several statistical models of English grammar, but their computational complexity makes applying them to large data sets int...
Abstract. This paper presents an architecture that enables the recognizer to learn incrementally and, thereby adapt to document image collections for performance improvement. We ar...
In this paper, we develop a geometric framework for linear or nonlinear discriminant subspace learning and classification. In our framework, the structures of classes are conceptu...
One of the most important steps in text processing and information retrieval is stemming—reducing of words to stems expressing their base meaning, e.g., bake, baked, bakes, bakin...
Alexander F. Gelbukh, Mikhail Alexandrov, Sang-Yon...