We introduce a framework for actively learning visual categories from a mixture of weakly and strongly labeled image examples. We propose to allow the categorylearner to strategic...
Recently, there has been an increasing interest in the investigation of statistical pattern recognition models for the fully automatic segmentation of the left ventricle (LV) of t...
Abstract We present an active learning framework that predicts the tradeoff between the effort and information gain associated with a candidate image annotation, thereby ranking un...
Users’ search needs are often represented by words and images are retrieved according to such textual queries. Annotation words assigned to the stored images are most useful to ...
Providing methods to support semantic interaction with growing volumes of video data is an increasingly important challenge for data mining. To this end, there has been some succes...