Learning visual classifiers for object recognition from weakly labeled data requires determining correspondence between image regions and semantic object classes. Most approaches u...
Object detection can be posted as those classification tasks where the rare positive patterns are to be distinguished from the enormous negative patterns. To avoid the danger of m...
The optimization method is one of key issues in discriminative learning of pattern classifiers. This paper proposes a hybrid approach of the Covariance Matrix Adaptation Evolution...
Choosing appropriate values for kernel parameters is one of the key problems in many kernel-based methods because the values of these parameters have significant impact on the per...
Abstract In this paper we present a new method for Joint Feature Selection and Classifier Learning (JFSCL) using a sparse Bayesian approach. These tasks are performed by optimizing...