Learning models for recognizing objects with few or no training examples is important, due to the intrinsic longtailed distribution of objects in the real world. In this paper, we...
Polysemy is a problem for methods that exploit image search engines to build object category models. Existing unsupervised approaches do not take word sense into consideration. We...
Many recent advances in complex domains such as Natural Language Processing (NLP) have taken a discriminative approach in conjunction with the global application of structural and...
This paper proposes a switching hypothesized measurements (SHM) model supporting multimodal probability distributions and presents the application of the model in handling potenti...
We introduce a novel set of features for robust object recognition. Each element of this set is a complex feature obtained by combining position- and scale-tolerant edgedetectors ...