—We present a novel framework to generate and rank plausible hypotheses for the spatial extent of objects in images using bottom-up computational processes and mid-level selectio...
In this paper we propose to use lexical semantic networks to extend the state-of-the-art object recognition techniques. We use the semantics of image labels to integrate prior kno...
Multi-label learning is useful in visual object recognition when several objects are present in an image. Conventional approaches implement multi-label learning as a set of binary...
We present a higher-level visual representation, visual synset, for object categorization. The visual synset improves the traditional bag of words representation with better discr...
Yantao Zheng, Ming Zhao 0003, Shi-Yong Neo, Tat-Se...
Current work in object categorization discriminates
among objects that typically possess gross differences
which are readily apparent. However, many applications
require making ...
Andrew Moldenke, Asako Yamamuro, David A. Lytle, E...