Evaluation of a CNN-Based Model for Predicting Human Psychological States Using Facial Features: Benefits and Limitations

Author(s)	Parth Sanjay Shinde, Nikhil Nandkishor Satpute, Siddhant Nitin Nimbalkar
Country	India
Abstract	This research evaluates the advantages and limitations of a CNN-based model for predicting human psychological states through facial analysis. This approach innovatively leverages CNNs to interpret facial expressions, which are essential for mental health assessment and human-computer interaction. The system provides an innovative approach to understanding human emotions by analysing facial expressions, a critical aspect of mental health assessment and human-computer interaction. However, while the method offers substantial advancements in emotion recognition, it faces challenges such as computational costs, dataset limitations, and an over-reliance on facial features. This paper explores the model's strengths and limitations, proposing improvements and suggesting directions for future research.
Keywords	Emotion Recognition, Convolutional Neural Networks, Psychological State Analysis, Facial Feature Extraction, Deep Learning, Real-time Processing
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 7, Issue 2, March-April 2025
Published On	2025-03-20
DOI	https://doi.org/10.36948/ijfmr.2025.v07i02.39356
Short DOI	https://doi.org/g89vvd

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