Abstract
Facial expression, age, and gender detection have received a lot of interest in recent years due to their wide range of applications in fields including healthcare, security, marketing, and entertainment. With the proliferation of artificial intelligence (AI) techniques, especially deep learning, facial analysis systems' accuracy and efficiency have improved significantly. This paper provides a comprehensive analysis of the most recent advances in AI-based facial expression, age, and gender identification algorithms. We explore the constraints and limitations of current techniques, such as the necessity for big annotated datasets, biases in training data, and interpretability issues in deep learning models. This study seeks to give academics, practitioners, and policymakers, a thorough grasp of the most recent state-of-the-art methodologies and trends in AI-based facial emotion, age, and gender identification, thereby supporting future advancements and responsible usage of these technologies. Keywords: Facial expression, age, gender, identification, deep learning, artificial intelligence
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
