… on machine learning and deep learning algorithms because they … emotion recognition.
They perform well in terms of classification, and they are more accurate at detecting emotions …

… algorithms for emotion recognition include … emotion recognition of four basic emotions (happiness,
sadness, anger and fear) from facial images. We have compared three deep-learning …

… A part of machine learning is deep learning where artificial neural networks … brain, learn
from large amounts of data. [11] Like how we learn from experience, the deep learning algorithm …

… and Google use deep learning techniques to solve … recognition, image recognition, 3-D
object recognition, and natural language processing. Some of the deep learning algorithms …

… in learning algorithms for intelligent systems by focusing on the emotion recognition problem…
We first present baseline outcomes for a cloud-based emotion recognition algorithm applied …

… that an accuracy of emotion recognition by Naïve Bayes was … emotion recognition algorithm
for basic emotions. This result can be helpful to provide the basis for the emotion recognition …

… Deep learning algorithm In this study, a deep learning algorithm is used to classify the
emotional EEG signals. The deep learning model contains two different units, namely, the …

… a review of emotional recognition of multimodal signals using deep learning and comparing
… Results show that the SVM algorithm has modified a lot to speech emotion recognition with …

… algorithms are used to separate human feelings into two positive and negative emotions. In
… -validation technique in this study of human emotion recognition using EEG signals. A data …

… Finally, we compare different ML and deep learning algorithms for emotion recognition
and suggest several open problems and future research directions in this exciting and fast-…