Boosting based detection methods have successfully been used for robust detection of faces and pedestrians. However, a very large amount of labeled examples are required for train...
Many real-world classification applications fall into the class of positive and unlabeled (PU) learning problems. In many such applications, not only could the negative training ex...
Learning a robust projection with a small number of training samples is still a challenging problem in face recognition, especially when the unseen faces have extreme variation in...
Creating a robust image classification system depends on having enough data with which one can adequately train and validate the model. If there is not enough available data, this...
Abstract. For many statistical pattern recognition methods, distributions of sample vectors are assumed to be normal, and the quadratic discriminant function derived from the proba...