Emotion Prediction Using Deep Learning

Now a day’s emotion prediction model plays an important role in computer communication system. Deep learning is emerging area in prediction of various tasks. Proposed method is used to predict human emotions using deep learning. Convolutional neural networks (CNNs) play an emerging role in identifying emotions from human expressions such as sad, happy, surprise, angry, neutral and fear. Proposed model employs FER 2013 and CK+ open source available datasets for training and testing to find emotion. Proposed research compared deep learning model with machine learning algorithms and achieved 95% accuracy is higher than existing methods. Model performance obtained from other performance metrics such as recall, precision and F1 score and accuracy shows better than existing methods. This research demonstrates how deep learning methods have the potential to transform emotion recognition software and make a significant contribution to the field of affective AI.

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