DeepEmoNet: An Efficient Deep Emotional Neural Network for Facial Expression Recognition

Recognizing human emotions is essential for successful interaction. This research focuses on applying deep learning techniques to identify emotions through facial expressions. Facial expressions reveal a lot about how individuals feel, making them extremely important for communication. The research focuses on developing a system that can look at facial photos and reliably determine the emotions being expressed. The primary objective was to distinguish between various emotions employing a deep learning approach. An accuracy level of approximately 88% was successfully attained by leveraging convolutional neural networks (CNNs). To conduct the analysis, the FER 2013 database was utilized, which contains grayscale images depicting facial expressions, each with dimensions of $48\times 48$ pixels.