The capability of measuring specific neurophysiological and autonomic parameters plays a
crucial role in the objective evaluation of a human's mental and emotional states. These …

This paper proposes an all-encompassing methodology called Strong Robust Copy-Move
Forgery Detection Network based on Layer-by-Layer Decoupling Refinement (DRNet) which …

Video content is rich in semantics and has the ability to evoke various emotions in viewers.
In recent years, with the rapid development of affective computing and the explosive growth …

Facial expressions have been proven to be the most effective way for the brain to recognize
human emotions in a variety of contexts. With the exponentially increasing research for …

Multimodal emotion recognition implies the use of different resources and techniques for
identifying and recognizing human emotions. A variety of data sources such as faces …

Video emotion recognition is an important branch of affective computing, and its solutions
can be applied in different fields such as human-computer interaction (HCI) and intelligent …

Facial expressions help in understanding the intentions of others as they are an essential
means of communication, revealing human emotions. Recently, thermal imaging has been …

With the expansion of machine learning and deep learning technology, facial expression
recognition methods have become more accurate and precise. However, in a real-case …

This paper evaluates timber defect classification performance across four various Local
Binary Patterns (LBP). The light and heavy timber used in the study are Rubberwood, KSK …

In this manuscript, multimodal emotion recognition using a decision-level fusion and feature-
level fusion approach is proposed. In the first approach, decision-level fusion approach is …