Deep learning applies multiple processing layers to learn representations of data with
multiple levels of feature extraction. This emerging technique has reshaped the research …

Recently, the automatic prediction of personality traits has received a lot of attention.
Specifically, personality trait prediction from multimodal data has emerged as a hot topic …

Passive image forgery detection methods that identify forgeries without prior knowledge
have become a key research focus. In copy-move forgery, the assailant intends to hide a …

Texture is a fundamental characteristic of many types of images, and texture representation
is one of the essential and challenging problems in computer vision and pattern recognition …

As one of the most comprehensive and objective ways to describe facial expressions, the
Facial Action Coding System (FACS) has recently received significant attention. Over the …

Abstract Local Binary Patterns (LBP) have emerged as one of the most prominent and
widely studied local texture descriptors. Truly a large number of LBP variants has been …

Biometrics systems have significantly improved person identification and authentication,
playing an important role in personal, national, and global security. However, these systems …

Land-use and land-cover (LULC) classification using remote sensing imagery plays a vital
role in many environment modeling and land-use inventories. In this study, a hybrid feature …

Binary feature descriptors such as local binary patterns (LBP) and its variations have been
widely used in many face recognition systems due to their excellent robustness and strong …

The limited capacity to recognise faces under occlusions is a long‐standing problem that
presents a unique challenge for face recognition systems and even humans. The problem …