Advances in object detection have made it possible to
collect large databases of certain objects. In this paper we
exploit these datasets for within-object classification. For
e...
Jania Aghajanian, Jonathan Warrell, Simon J.D. Pri...
Background: Cancer diagnosis and clinical outcome prediction are among the most important emerging applications of gene expression microarray technology with several molecular sig...
Alexander R. Statnikov, Lily Wang, Constantin F. A...
The classification performance of nearest prototype classifiers largely relies on the prototype learning algorithms, such as the learning vector quantization (LVQ) and the minimum...
This paper presents a new method for viewpoint invariant pedestrian recognition problem. We use a metric learning framework to obtain a robust metric for large margin nearest neigh...
Mert Dikmen, Emre Akbas, Thomas S. Huang, Narendra...
In this paper we study how to improve nearest neighbor classification by learning a Mahalanobis distance metric. We build on a recently proposed framework for distance metric lear...