The main idea of this ISO is to use StarGAN (A type of GAN model) to perform training and
testing on an emotion dataset resulting in a emotion recognition which can be generated by …

In the field of facial expression recognition, deep learning is extensively used. However,
insufficient and unbalanced facial training data in available public databases is a major …

Emotion generation has remained a challenging task due to the high similarity between
each emotion class. In addition, the model had to learn images with various lighting …

The detection of human emotions has applicability in various domains such as assisted
living, health monitoring, domestic appliance control, crowd behavior tracking real time, and …

Faces and their expressions are one of the potent subjects for digital images. Detecting
emotions from images is an ancient task in the field of computer vision; however, performing …

For our CS229 project, we studied the problem of reliable computerized emotion recognition
in images of human faces. First, we performed a preliminary exploration using SVM …

During communication process, people's emotions are usually shown on the face (we call it
expression). Capturing expression signals is very important to communication among …

We propose different approach combinations including GANs and image transformation in
facial emotion classification especially for FER-2013 dataset. Our goal is not to reach the …

In the realm of emotion synthesis, the ability to create authentic and nuanced facial
expressions continues to gain importance. The GANmut study discusses a recently …

In this project we applied various deep learning methods (convolutional neural networks) to
identify the key seven human emotions: anger, disgust, fear, happiness, sadness, surprise …