Feature Extraction with Handcrafted Methods and Convolutional Neural Networks for Facial Emotion Recognition

Feature Extraction with Handcrafted Methods and Convolutional Neural Networks for Facial Emotion Recognition

This research compares the facial expression recognition accuracy achieved using image features extracted (a) manually through handcrafted methods and (b) automatically through convolutional neural networks (CNNs) from different depths, with and without retraining. The Karolinska Directed Emotional...

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Bibliographic Details
Main Authors: Eleni Tsalera, Andreas Papadakis, Maria Samarakou, Ioannis Voyiatzis
Format: Article
Language:English
Published: MDPI AG 2022-08-01
Series:Applied Sciences
Subjects:
convolutional neural network
facial emotion recognition
feature extraction
histogram of oriented gradients
local binary patterns
transfer learning
Online Access:https://www.mdpi.com/2076-3417/12/17/8455

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https://www.mdpi.com/2076-3417/12/17/8455

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