We propose a sparse non-negative image coding based on simulated annealing and matrix pseudo-inversion. We show that sparsity and non-negativity are both important to obtain part-...
Sparse representation of signals has been the focus of much research in the recent years. A vast majority of existing algorithms deal with vectors, and higher
Ravishankar Sivalingam, Daniel Boley, Vassilios Mo...
In this letter we explore an alternative structural representation for Steinbuch-type binary associative memories. These networks offer very generous storage capacities (both asy...
NIMFA is an open-source Python library that provides a unified interface to nonnegative matrix factorization algorithms. It includes implementations of state-of-the-art factoriza...
In this paper, we present a multi-label sparse coding
framework for feature extraction and classification within
the context of automatic image annotation. First, each image
is ...
Changhu Wang (University of Science and Technology...