A Review of the Deep Convolutional Neural Networks for the Analysis of Facial Expressions

A Review of the Deep Convolutional Neural Networks for the Analysis of Facial Expressions

Facial expression recognition has acquired much renouncement in recent years and is used in multiple fields of image process¬ing, emotion detection, depression detection, criminal record findings, and medical-related fields. Facial expression recognition systems have revolutionized the field of emotion detection by allowing machines to identify and interpret human emotions, opening new avenues of research in deep learning and providing insight into the potential of artificial intelligence to understand and analyze human emotions. This study aims to thoroughly review Facial expression recognition systems, including an assessment of different methodologies and publicly available databases used in Facial expression recognition studies. Apart from the ability to diagnose emotional expressions distantly, the proposed face recognition model has potential uses in telemedicine and mental health diagnosis. All these developments are summarized, which additionally draws attention to their wider implications for healthcare services. This paper also investigates cutting-edge facial emotion identification approaches, especially deep learning and convolutional networks.