This study presents a systematic review of the automatic vision-based assessment systems
and models from related fields over the last 6 years. Many studies focus on automatic vision …

The weight-adapted convolution neural network (WACNN) is proposed to extract
discriminative expression representations for recognizing facial expression. It aims to make …

In facial expression recognition applications, the classification accuracy decreases because
of the blur, illumination and localization problems in images. Therefore, a robust emotion …

In this paper, a novel Monogenic Sobel Directional Pattern (MSDP) using fractional order
masks is proposed for extracting features. The MSDP uses fractional-order Sobel masks to …

One of the key challenge issues of deep-learning-based facial expression recognition (FER)
is learning effective and robust features from variant samples. In this paper, Region-based …

Emotions have a great significance in human-to-human and in human-to-computer
communication and interaction. In this paper, an effective and novel approach to recognize …

The visual representations created using the self-distillation paradigm of Bootstrap Your
Emotion Latent (BYEL) are empirically found to be less evenly distributed than those created …

In facial expression recognition applications, the images are corrupted with random noise,
and this affects the classification accuracy. This article proposes a maximum and Minimum …

It is necessary to recognize the target in the situation of military battlefield monitoring and
civilian real‐time monitoring. Sparse representation‐based SAR image target recognition …

Various machine learning technologies and artificial intelligence techniques were applied
on different applications of dentistry. Caries detection in orthodontics is a very much needed …