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- W3091090967 abstract "This paper outlines the effectiveness of several popular machine learning algorithms for facial expression recognition. The dataset used for this paper consists of 35887 images of size 48×48 pixels which are all depicting faces posed in one of seven expressions (anger, disgust, fear, happy, sad, surprise, neutral). This is a popularly used dataset for practice and exploration and there are many different approaches suggested in the literature. In this paper, the following algorithms are applied and tested: AdaBoost, Logistic Regression, Dense Neural Network (DNN), and Convolutional Neural Network (CNN). CNN is shown to provide the highest accuracy compared to other algorithms." @default.
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- W3091090967 date "2020-07-01" @default.
- W3091090967 modified "2023-10-10" @default.
- W3091090967 title "Machine Learning Approach for Facial Expression Recognition" @default.
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- W3091090967 doi "https://doi.org/10.1109/eit48999.2020.9208316" @default.
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