Automatic understanding of human affect using visual signals is of great importance in
everyday human–machine interactions. Appraising human emotional states, behaviors and …

Abstract The Affect-in-the-Wild (Aff-Wild) Challenge proposes a new comprehensive
benchmark for assessing the performance of facial affect/behaviour analysis …

Human visual perception is efficient, flexible and context-sensitive. The Bayesian brain view
explains this with probabilistic perceptual inference integrating prior experience and …

Featured Application In this paper, Deep Learning has been used to classify, predict early
nutrient deficiencies during the growth of tomato plant. This study can be applied to …

This article introduces BReG-NeXt, a residual-based network architecture using a function
wtih bounded derivative instead of a simple shortcut path (aka identity mapping) in the …

Since most facial emotion recognition (FER) methods significantly rely on supervision
information, they have a limit to analyzing emotions independently of persons. On the other …

Emotions represent a key aspect of human life and behavior. In recent years, automatic
recognition of emotions has become an important component in the fields of affective …

When a person recognizes another's emotion, he or she recognizes the (facial) features
associated with emotional expression. So, for a machine to recognize facial emotion (s), the …

Identity-invariant facial expression recognition (FER) has been one of the challenging
computer vision tasks. Since conventional FER schemes do not explicitly address the inter …

Human emotion detection is one of the major problems in computer vision. Human emotions
consist of several sub-emotions which are difficult to classify into a specific class. In this …