In this paper, we propose our Correlation For Completion Network (CFCNet), an end-to-end
deep learning model that uses the correlation between two data sources to perform sparse …

Despite considerable advances made in face recognition in recent years, the recognition
performance still suffers from insufficient training samples. Hence, various algorithms have …

The face plays an essential role in identifying people and showing their emotions in society.
The human ability to recognize faces is remarkable. But face recognition is a fundamental …

Signal variation in diffusion-weighted images (DWIs) is influenced both by thermal noise and
by spatially and temporally varying artifacts, such as rigid-body motion and cardiac …

To understand human behavior, a fundamental aspect is the analysis of the face and
movement. This aspect is particularly important in the context of sales, where to know the …

Algorithms for projection of digital images into their eigensubspaces in the framework of
linear methods PCA, LDA, PLS and CCA are considered. The history of these methods …

Paper presents the method of two-dimensional canonical correlation analysis (2DCCA)
applied to image processing and biometrics. Method is based on representing the image as …

This paper presents the implementation of the method of twodimensional Canonical
Correlation Analysis (CCA) and two-dimensional Partial Least Squares (PLS) applied to …

In this paper, a novel packet classification scheme optimized for multi-core network
processors is proposed. The algorithm, Explicit Cuttings (ExpCuts), adopts a hierarchical …

Local binary patterns (LBPs) are very commonly used to determine if a face in an image is a
known person. However, accuracy is generally proportional to the number of training …