Emotion Recognition Using CNN

In this research paper, we assess the efficacy of different Convolutional Neural Network (CNN) models, which are powerful tools for solving the image recognition problem. More specifically, we will concentrate on how to use deep learning along with OpenCV and Python to identify and recognize human facial expressions. This study explores how effectively combining OpenCV libraries in Python with deep learning can be achieved for human face detection and the analysis of their emotional states. The proposed framework is intended to recognize human faces and classify their emotions in real time, making it suitable for many platforms such as computers, smartphones, and various software applications. Human-machine interaction depends on emotion recognition, as it helps AI systems understand and react to human emotions. This paper discusses advances and methods for emotion recognition, including speech, hand and body gestures, and facial expressions. The main objective of this study is to suggest a suitable real-time emotion recognition strategy based on CNN-based deep learning models that will improve the accuracy and applicability of emotion recognition in different environments.