A successful detection and classification system must have two properties: it should be general enough to compensate for intra-class variability and it should be specific enough to...
We present a novel framework for multi-label learning that explicitly addresses the challenge arising from the large number of classes and a small size of training data. The key a...
This paper presents a method for automatically estimating human interruptibility in home environments. To make online remote communication smoother, determining if it is appropria...
Abstract. We present a possibly great improvement while performing semisupervised learning tasks from training data sets when only a small fraction of the data pairs is labeled. In...
Recognition of 3D objects from different viewpoints is a difficult problem. In this paper, we propose a new method to recognize 3D range images by matching local surface descripto...