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Facial emotion recognition (FER) refers to the process of identifying and classifying human emotions based on facial expressions . By analyzing facial features and patterns, machines can make educated guesses about a person's emotional state. This subfield of facial recognition is highly interdisciplinary, drawing on insights from computer vision, machine learning, and psychology.
In this research article, we will try to understand the concept of facial emotion recognition from both a philosophical and technical perspective. We will also explore a custom VGG13 model architecture and the revolutionary Facial Expression Recognition Plus (FER+) dataset to build a unified real-time facial emotion recognition system. Finally, we will also analyze the results obtained experimentally.