We propose an unsupervised, probabilistic method for learning visual feature hierarchies. Starting from local, low-level features computed at interest point locations, the method c...
— We propose a new approach to the problem of schema matching in relational databases that merges the hybrid and composite approach of combining multiple individual matching tech...
The optimal spatial adaptation (OSA) method [1] proposed by Boulanger and Kervrann has proven to be quite effective for spatially adaptive image denoising. This method, in additio...
The image of a curved, specular (mirror-like) surface is a distorted reflection of the environment. The goal of our work is to develop a framework for recovering general shape fr...
Recently, sparse coding has been receiving much attention in object and scene recognition tasks because of its superiority in learning an effective codebook over k-means clusterin...