The Relevance Vector Machine (RVM) is a sparse approximate Bayesian kernel method. It provides full predictive distributions for test cases. However, the predictive uncertainties ...
We present a novel method for inferring three-dimensional shape from a collection of defocused images. It is based on the observation that defocused images are the null-space of ce...
Today many kinds of postprocessing are used in digital TV receivers or multimedia terminals for video signals to enhance the picture quality. To achieve this the properties of hum...
The wide availability of large scale databases requires more efficient and scalable tools for data understanding and knowledge discovery. In this paper, we present a method to ...
Duy-Dinh Le, Shin'ichi Satoh, Michael E. Houle, Da...
We study in this paper the problem of bridging the semantic gap between low-level image features and high-level semantic concepts, which is the key hindrance in content-based imag...