Abstract Hyperspectral Image Processing (HSIP) is an essential technique in remote
sensing. Currently, extensive research is carried out in hyperspectral image processing …

A well-known shortcoming of the traditional canonical correlation analysis (CCA) is the lack
of robustness against outliers. This shortcoming hinders the application of CCA in the case …

Over the past two decades, there has been a notable increase in the complexity and
dynamism of industrial and manufacturing systems. Traditional fault detection strategies …

For reliable and accurate multimodal biometric based person verification, demands an
effective discriminant feature representation and fusion of the extracted relevant information …

Dear Editor, A global and local canonical correlation analysis (GLCCA) based on data-
driven is presented for underwater positioning. Underwater positioning technology can help …

Two-directional two-dimensional canonical correlation analysis ((2D) CCA) directly seeks
linear relationship between different image data sets without reshaping images into vectors …

Set-based video recognition is an important application in practice, and many specialized
approaches have been proposed. However, most of these methods either only use one kind …

Feature extraction is one of the fundamental problems in pattern recognition research. For
image recognition, extracting effective image features is the key to accomplish the …

Supervised fractional-order embedding multiview canonical correlation analysis via ordinal
label dequantization (SFEMCCA-OLD) for image interest estimation is presented in this …

Multi-modal Canonical Correlation Analysis (MCCA) is an important information fusion
method, and some discriminant variations of MCCA have been proposed. However, the …