Multi-view graph-based clustering aims to provide clustering solutions to multi-view data.
However, most existing methods do not give sufficient consideration to weights of different …

Palmprint recognition has been widely used in security authentication. However, most of the
existing palmprint representation methods are focused on a special application scenario …

Discriminative correlation filters (DCFs) have been widely used in the tracking community
recently. DCFs-based trackers utilize samples generated by circularly shifting from an image …

Feature selection for multiple types of data has been widely applied in mild cognitive
impairment (MCI) and Alzheimer's disease (AD) classification research. Combining multi …

Multi-view semi-supervised learning (SSL) has attracted great attention due to its
effectiveness in information utilization of multiple views and labeled and unlabeled data to …

Cross-view classification that means to classify samples from heterogeneous views is a
significant yet challenging problem in computer vision. An effective solution to this problem …

Multi-view visual classification methods have been widely applied to use discriminative
information of different views. This strategy has been proven very effective by many …

Dimensionality reduction is an important step in increasing the performance of machine
learning algorithms while decreasing the processing time. From feature reduction …

Biometric system has been widely adopted for human verification or identification, so
inherently it requires the characteristics like high security, accuracy and acceptability …

Faced with the increasing data diversity and dimensionality, multi-view dimensionality
reduction has been an important technique in computer vision, data mining and multi-media …