Face Emotion Detection using Deeplearning - Convolutional Neural Networks and OpenCV

Published: 10 August 2022
on channel: Smart AI Technologies

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In this video Convolutional Neural Network (CNN) or Deeplearning for Facial emotion recognition/Detection is proposed which uses pre-processing stages and CNN topologies to improve accuracy and training time. Sadness, happiness, contempt, anger, fear, surprise, and neutral are the seven primary human emotions anticipated. The model will be tested using the Facial Expression database as well as other facial positions. To avoid bias towards a specific group of photos from a database, performance will be evaluated using cross-validation techniques. Proposed system was trained using a huge database consisting of around 21,000 images. Using our personal system, training time for the proposed model was drastically reduced to 4hours for 20 epochs.

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