With the transition of facial expression recognition (FER) from laboratory-controlled to
challenging in-the-wild conditions and the recent success of deep learning techniques in …

With the advancements in machine and deep learning algorithms, the envision of various
critical real-life applications in computer vision becomes possible. One of the applications is …

Deep learning models have gained a reputation of high accuracy in many domains.
Convolutional Neural Networks (CNN) are specialized towards image recognition and have …

Current state-of-the-art models for automatic facial expression recognition (FER) are based
on very deep neural networks that are effective but rather expensive to train. Given the …

Often, emotional disorders are overlooked due to their lack of awareness, resulting in
potential mental issues. Recent advances in sensing and inference technology provide a …

This paper proposes the design of a Facial Expression Recognition (FER) system based on
deep convolutional neural network by using facial parts. In this work, a simple solution for …

Emotion being a subjective thing, leveraging knowledge and science behind labeled data
and extracting the components that constitute it, has been a challenging problem in the …

Facial expression recognition is very useful for effective human–computer interaction, robot
interfaces, and emotion-aware smart agent systems. This paper presents a new framework …

Facial expression recognizers based on handcrafted features have achieved satisfactory
performance on many databases. Recently, deep neural networks, eg deep convolutional …

This paper proposes a method of accurately assessing image quality without a reference
image by using a deep convolutional neural network. Existing training based methods …