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Facial expression recognition and computer vision is based on deep learning technology and convolutional neural network. Whether it is two-stage target detection or single-stage target detection, performance of algorithm is measured by detection speed and accuracy.
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The research of facial expression recognition mainly includes two categories: traditional methods and deep learning methods. Traditional facial expression ...
The main aim of the proposed model is to detect five different facial expressions, viz. Angry, Happy, Neutral, Sad, and Surprise. The proposed model is built ...
The current deep facial expression recognition system is committed to solve the following two problems: (1) Overfitting due to lack of sufficient training data; ...
Deep learning is a new area of research within machine learning method which can classify images of human faces into emotion categories using Deep Neural ...
Oct 19, 2021 · Owing to the wide range of applications, Facial Expression Recognition (FER) is considered an important research topic in the research ...
Jan 6, 2022 · Abstract. Background and objective: Facial expression recognition technology will play an increasingly important role in our daily life.
Facial Expression Recognition (FER) is a computer vision task aimed at identifying and categorizing emotional expressions depicted on a human face.
Section 4 proposes Micro-Facial Expression Based Deep-Rooted Learning (MFEDRL) classifier. Performance evaluation metrics are described in Section 5 Results of ...
Feb 27, 2023 · A deep learning approach is presented to classify happy, sad, angry, fearful, contemptuous, surprised and disgusted expressions. Accurate ...