Facial Emotion Recognition with Convolutional Neural Networks using DL

In this universe, facial expressions reveal a person's mood. One thing is certain: every expression expresses feelings. Artificial intelligence (AI) lets us distinguish a variety of emotions, even though everyone has a unique set of facial features and emotional repertoire. Face emotion-recognition AIs can be built using deep learning. Create a convolutional neural network (CNN) to train the dataset and get high prediction accuracy using this method. The goal is to identify seven basic face expressions among hundreds. Happy, sad, neutral, anger, surprise, fear, and contempt are the most common facial expressions, followed by neutrality. This facial expression identification can be done using deep face algorithms, machine learning, other AI methods, TensorFlow, etc. Our model is 70%-80% accurate. This method may be the easiest and most effective.