In genomic sequence analysis tasks like splice site recognition or promoter identification, large amounts of training sequences are available, and indeed needed to achieve suffici...
Machine Learning techniques are successfully applied to establish quantitative relations between chemical structure and biological activity (QSAR), i.e. classify compounds as activ...
A number of machine learning (ML) techniques have recently been proposed to solve color constancy problem in computer vision. Neural networks (NNs) and support vector regression (...
Adaptive tracking-by-detection methods are widely used in computer vision for tracking arbitrary objects. Current approaches treat the tracking problem as a classification task a...
Multi-instance learning and semi-supervised learning are different branches of machine learning. The former attempts to learn from a training set consists of labeled bags each con...