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...
Within a long-term distributed systems project we repeatedly stumbled across the well-known yet difficult question to either implement from scratch or comprehend and adapt existin...
Sparse grid methods represent a powerful and efficient technique for the representation and approximation of functions and particularly the solutions of partial differential equat...
Recently SVMs using spatial pyramid matching (SPM)
kernel have been highly successful in image classification.
Despite its popularity, these nonlinear SVMs have a complexity
O(n...
Jianchao Yang, Kai Yu, Yihong Gong, Thomas S. Huan...
Adaptive sparse coding methods learn a possibly overcomplete set of basis functions, such that natural image patches can be reconstructed by linearly combining a small subset of t...