Facial expression recognition using computer vision: A systematic review
Emotion recognition has attracted major attention in numerous fields because of its relevant
applications in the contemporary world: marketing, psychology, surveillance, and …
applications in the contemporary world: marketing, psychology, surveillance, and …
Emotional expression in psychiatric conditions: New technology for clinicians
K Grabowski, A Rynkiewicz, A Lassalle… - Psychiatry and …, 2019 - Wiley Online Library
Aim Emotional expressions are one of the most widely studied topics in neuroscience, from
both clinical and non‐clinical perspectives. Atypical emotional expressions are seen in …
both clinical and non‐clinical perspectives. Atypical emotional expressions are seen in …
Deploying machine learning techniques for human emotion detection
Emotion recognition is one of the trending research fields. It is involved in several
applications. Its most interesting applications include robotic vision and interactive robotic …
applications. Its most interesting applications include robotic vision and interactive robotic …
Facial expression recognition for monitoring neurological disorders based on convolutional neural network
Facial expressions are a significant part of non-verbal communication. Recognizing facial
expressions of people with neurological disorders is essential because these people may …
expressions of people with neurological disorders is essential because these people may …
Deep convolutional BiLSTM fusion network for facial expression recognition
Deep learning algorithms have shown significant performance improvements for facial
expression recognition (FER). Most deep learning-based methods, however, focus more …
expression recognition (FER). Most deep learning-based methods, however, focus more …
Learning deep facial expression features from image and optical flow sequences using 3D CNN
Facial expression is highly correlated with the facial motion. According to whether the
temporal information of facial motion is used or not, the facial expression features can be …
temporal information of facial motion is used or not, the facial expression features can be …
Deeper cascaded peak-piloted network for weak expression recognition
Facial expression recognition is in general a challenging problem, especially in the
presence of weak expression. Most recently, deep neural networks have been emerging as …
presence of weak expression. Most recently, deep neural networks have been emerging as …
Facial emotion detection using modified eyemap–mouthmap algorithm on an enhanced image and classification with tensorflow
A Joseph, P Geetha - The Visual Computer, 2020 - Springer
Detection of emotion using facial expression is a growing field of research. Facial
expression detection is also helpful to identify the behavior of a person when a man interacts …
expression detection is also helpful to identify the behavior of a person when a man interacts …
A multi-scale and rotation-invariant phase pattern (MRIPP) and a stack of restricted Boltzmann machine (RBM) with preprocessing for facial expression classification
AS Alphonse, K Shankar… - Journal of Ambient …, 2021 - Springer
In facial expression recognition applications, the classification accuracy decreases because
of the blur, illumination and localization problems in images. Therefore, a robust emotion …
of the blur, illumination and localization problems in images. Therefore, a robust emotion …
Multi-modal Expression Detection (MED): A cutting-edge review of current trends, challenges and solutions
In the process of day-to-day learning, expressions are very vital. Detection of human
expressions is growing and has caught the interest of many researchers in the past few …
expressions is growing and has caught the interest of many researchers in the past few …