Exploring Facial Emotion Recognition (FER) Using Convolutional Neural Networks

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If utilised efficiently, computerised emotional recognition softwares can be used for many different purposes and in many different settings. Education systems, healthcare systems, and even the marketing fields are some fields amongst many which can greatly benefit from a technological advantage such as this to help service or improve the individuals involved. Having access to such data can tell so much about a person’s wants, needs, and desires based on their psychological state, whether they are excited, in pain, feeling frustrated, crying, laughing, or even feeling nothing. This software is made with the intent of understanding the needs of individuals who may not know how to express them themselves using words, but rather by their external facial expressions. By using advanced technology, we can create a machine smart enough to determine these needs for us, thus helping all parties involved. This research proposal explores several key features of human facial extraction techniques with different deep learning algorithms to explore emotional recognition. Some of the technologies and libraries I’ve decided to use are OpenCV, NumPy, MatPlotLib, amongst others, and I am mainly using the language Python to help me achieve my vision.

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Kulcsszavak
Convolutional Neural Networks, Face Recognition, Computer Vision, Python, Artificial Intelligence, Machine Learning
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