Active learning methods aim to select the most informative unlabeled instances to label first, and can help to focus image or video annotations on the examples that will most impr...
Detecting objects in cluttered scenes and estimating articulated human body parts are two challenging problems in computer vision. The difficulty is particularly pronounced in ac...
We consider the problem of deep web source selection and argue that existing source selection methods are inadequate as they are based on local similarity assessment. Specificall...
We present a modular approach to implement adaptive decisions with existing scientific codes. Using a sophisticated system software tool based on the function call interception t...
Pilsung Kang 0002, Yang Cao, Naren Ramakrishnan, C...
We propose a novel cost-efficient approach to threshold selection for binary web-page classification problems with imbalanced class distributions. In many binary-classification ta...