Motivated by image reconstruction, sparse representation based classification (SRC) has
been shown to be an effective method for applications like face recognition. In this paper, we …

As one of the most popular research topics, sparse representation and dictionary learning
technique has received an increasing amount of interest in recent years. Sparse …

Supervised sparse coding has become a widely-used module in existing recognition
systems, which unifies classifier training and dictionary learning to enforce discrimination in …

The employed dictionary plays an important role in sparse representation or sparse coding
based image reconstruction and classification, while learning dictionaries from the training …

Dictionary learning (DL), playing a key role in the success of sparse representation, has led
to state-of-the-art results in image classification tasks. Among the existing supervised …

We present an online semi-supervised dictionary learning algorithm for classification tasks.
Specifically, we integrate the reconstruction error of labeled and unlabeled data, the …

In recent years, sparse representation has been widely used in object recognition
applications. How to learn the dictionary is a key issue to sparse representation. A popular …

For sparse representation or sparse coding based image classification, the dictionary, which
is required to faithfully and robustly represent query images, plays an important role on its …

Conventional dictionary learning algorithms suffer from the following problems when applied
to face recognition. First, since in most face recognition applications there are only a limited …

In sparse dictionary learning based face recognition (FR), a discriminative dictionary is
learned from the training set so that good classification performance can be achieved on …