Attributes are visual concepts that can be detected by machines, understood by humans, and shared across categories. They are particularly useful for fine-grained domains where c...
Kun Duan, Devi Parikh, David J. Crandall, Kristen ...
In this paper, we consider the problem of speaker verification as a two-class object detection problem in computer vision, where the object instances are 1-D short-time spectral v...
In this paper we propose a novel computational method to infer visual saliency in images. The computational method is based on the idea that salient objects should have local char...
The general approach for automatically driving data collection using information from previously acquired data is called active learning. Traditional active learning addresses the...
This paper proposes a diagnosis architecture that integrates consistency based diagnosis with induced time series classifiers, trying to combine the advantages of both methods. Co...