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Facial Expression Recognition by Using Multifeatured Fusion And Deep Learning Techniques

Ch. Srividya, N. Shalini, N. V. Krishna Rao, G. Sucharitha Reddy, Agutla Ruchitha, Garlapati Sirisha

Abstract


In our daily lives, sentiment analysis is a vital part of communication. A vital component is information regarding how the user feels when someone communicates. You will need a solution that can handle everything from recognizing a user's emotional state to personalizing the user experience. This study's objective is to look into emotions. Today, deep learning techniques are quickly advancing in a variety of fields, including computer vision. Without a doubt, a convolutional neural network (CNN) model can analyse a photo and recognize facial emotions. Create a method that takes into account Understudy's external emotions. The FER2013 database contains seven behaviours in three phases: Hear Falls face recognition, standardization, and CNN emotion recognition. Teachers may customize their greetings to their students' moods, according to the research, and face expression detection can be taught.


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References


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