Set-Based Discriminative Measure for Electrocardiogram Beat Classification

Set-Based Discriminative Measure for Electrocardiogram Beat Classification

Computer aided diagnosis systems can help to reduce the high mortality rate among cardiac patients. Automatical classification of electrocardiogram (ECG) beats plays an important role in such systems, but this issue is challenging because of the complexities of ECG signals. In literature, feature designing has been broadly-studied. However, such methodology is inevitably limited by the heuristi...

Electrocardiogram Beat Classification using Probabilistic Neural Network

The Electrocardiogram (ECG) plays significant role in assessing patients with abnormal activity in their heart. ECG recordings of the patient taken to analyze abnormality and classify type of disorder present in the heart functionality. An Electrocardiogram is a bioelectrical signal that records the heart’s electrical activity versus time. It is used to measure the rate and regularity of heartb...

Set Based Discriminative Ranking for Recognition

Recently both face recognition and body-based person reidentification have been extended from single-image based scenarios to video-based or even more generally image-set based problems. Set-based recognition brings new research and application opportunities while at the same time raises great modeling and optimization challenges. How to make the best use of the available multiple samples for e...

Prototype Discriminative Learning for Face Image Set Classification

Discriminative Learning of the Prototype Set for Nearest Neighbor Classification

The nearest neighbor rule is one of the most widely used models for classification and selecting a compact set of prototype instances is an important problem for its applications. Many existing approaches on the prototype selection problem rely on instance-based analyses and local criteria on the class distribution, which are intractable for numerical optimization techniques. In this paper, we ...