This paper proposes a data driven image segmentation algorithm, based on decomposing the target output (ground truth). Classical pixel labeling methods utilize machine learning al...
This paper introduces a novel way to leverage the implicit geometry of sparse local features (e.g. SIFT operator) for the purposes of object detection and segmentation. A two-clas...
With the rapid technological advances in machine learning and data mining, it is now possible to train computers with hundreds of semantic concepts for the purpose of annotating i...
Linear Discriminant Analysis (LDA) has been a popular method for extracting features which preserve class separability. It has been widely used in many fields of information proces...
Traditionally, machine learning algorithms have been evaluated in applications where assumptions can be reliably made about class priors and/or misclassification costs. In this pa...