Detecting living-skin tissue in a video on the basis of induced color changes due to blood
pulsation is emerging for automatic region of interest localization in remote …

For an object classification system, the most critical obstacles toward real-world applications
are often caused by large intra-class variability, arising from different lightings, occlusion …

Unconstrained face recognition is still an open problem as the state-of-the-art algorithms
have not yet reached high recognition performance in real-world environments. This paper …

In image classification, obtaining adequate data to learn a robust classifier has often proven
to be difficult in several scenarios. Classification of histological tissue images for health care …

Dictionary learning has played an important role in the success of sparse representation.
Although discriminative synthesis dictionary learning for sparse representation with a high …

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 …

The lack of labeled data presents a common challenge in many computer vision and
machine learning tasks. Semisupervised learning and transfer learning methods have been …

Recently, many sparse coding based approaches have been proposed for human action
recognition. However, most of them focus on learning a discriminative dictionary without …

In the training stage of radial basis function (RBF) networks, we need to select some suitable
RBF centers first. However, many existing center selection algorithms were designed for the …

Image fusion is widely used in different areas and can integrate complementary and relevant
information of source images captured by multiple sensors into a unitary synthetic image …