Most works based on diversity suggest that there exists only weak correlation between diversity and ensemble accuracy. We show that by combining the diversities with the classifica...
Albert Hung-Ren Ko, Robert Sabourin, Alceu de Souz...
We achieve two goals in this paper: (1) to build a novel appearance-based object representation that takes into account variations in contrast often found in training images; (2) ...
Chakra Chennubhotla, Allan D. Jepson, John Midgley
The problem of model selection is considerably important for acquiring higher levels of generalization capability in supervised learning. In this paper, we propose a new criterion ...
In this paper, we present a novel maximum correlation sample subspace method and apply it to human face detection [1] in still images. The algorithm starts by projecting all the t...
Recently, several manifold learning algorithms have been proposed, such as ISOMAP (Tenenbaum et al., 2000), Locally Linear Embedding (Roweis & Saul, 2000), Laplacian Eigenmap ...