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Detection of Mild Cognitive Impairment Using Facial Features in Video Conversations
Muath Alsuhaibani, Hiroko H. Dodge, Mohammad H. Mahoor
Early detection of Mild Cognitive Impairment (MCI) leads to early interventions to slow the progression from MCI into dementia. Deep Learning (DL) algorithms could help achieve ear…
MC-ViViT: Multi-branch Classifier-ViViT to detect Mild Cognitive Impairment in older adults using facial videos
Jian Sun, Hiroko H. Dodge, Mohammad H. Mahoor
Deep machine learning models including Convolutional Neural Networks (CNN) have been successful in the detection of Mild Cognitive Impairment (MCI) using medical images, questionna…
GANalyzer: Analysis and Manipulation of GANs Latent Space for Controllable Face Synthesis
Ali Pourramezan Fard, Mohammad H. Mahoor, Sarah Ariel Lamer +1
Generative Adversarial Networks (GANs) are capable of synthesizing high-quality facial images. Despite their success, GANs do not provide any information about the relationship bet…
Facial Landmark Points Detection Using Knowledge Distillation-Based Neural Networks
Ali Pourramezan Fard, Mohammad H. Mahoor
Facial landmark detection is a vital step for numerous facial image analysis applications. Although some deep learning-based methods have achieved good performances in this task, t…
XnODR and XnIDR: Two Accurate and Fast Fully Connected Layers For Convolutional Neural Networks
Jian Sun, Ali Pourramezan Fard, Mohammad H. Mahoor
Capsule Network is powerful at defining the positional relationship between features in deep neural networks for visual recognition tasks, but it is computationally expensive and n…
ASMNet: a Lightweight Deep Neural Network for Face Alignment and Pose Estimation
Ali Pourramezan Fard, Hojjat Abdollahi, Mohammad Mahoor
Active Shape Model (ASM) is a statistical model of object shapes that represents a target structure. ASM can guide machine learning algorithms to fit a set of points representing a…
BReG-NeXt: Facial Affect Computing Using Adaptive Residual Networks With Bounded Gradient
Behzad Hasani, Pooran Singh Negi, Mohammad H. Mahoor
This paper introduces BReG-NeXt, a residual-based network architecture using a function wtih bounded derivative instead of a simple shortcut path (a.k.a. identity mapping) in the r…
Bounded Residual Gradient Networks (BReG-Net) for Facial Affect Computing
Behzad Hasani, Pooran Singh Negi, Mohammad H. Mahoor
Residual-based neural networks have shown remarkable results in various visual recognition tasks including Facial Expression Recognition (FER). Despite the tremendous efforts have…
Leveraging Class Similarity to Improve Deep Neural Network Robustness
Pooran Singh Negi, David chan, Mohammad Mahoor
Traditionally artificial neural networks (ANNs) are trained by minimizing the cross-entropy between a provided groundtruth delta distribution (encoded as one-hot vector) and the AN…
AffectNet: A Database for Facial Expression, Valence, and Arousal Computing in the Wild
Ali Mollahosseini, Behzad Hasani, Mohammad H. Mahoor
Automated affective computing in the wild setting is a challenging problem in computer vision. Existing annotated databases of facial expressions in the wild are small and mostly c…
Facial Affect Estimation in the Wild Using Deep Residual and Convolutional Networks
Behzad Hasani, Mohammad H. Mahoor
Automated affective computing in the wild is a challenging task in the field of computer vision. This paper presents three neural network-based methods proposed for the task of fac…
Facial Expression Recognition Using Enhanced Deep 3D Convolutional Neural Networks
Behzad Hasani, Mohammad H. Mahoor
Deep Neural Networks (DNNs) have shown to outperform traditional methods in various visual recognition tasks including Facial Expression Recognition (FER). In spite of efforts made…
Spatio-Temporal Facial Expression Recognition Using Convolutional Neural Networks and Conditional Random Fields
Behzad Hasani, Mohammad H. Mahoor
Automated Facial Expression Recognition (FER) has been a challenging task for decades. Many of the existing works use hand-crafted features such as LBP, HOG, LPQ, and Histogram of…
An FFT-based Synchronization Approach to Recognize Human Behaviors using STN-LFP Signal
Hosein M. Golshan, Adam O. Hebb, Sara J. Hanrahan +2
Classification of human behavior is key to developing closed-loop Deep Brain Stimulation (DBS) systems, which may be able to decrease the power consumption and side effects of the…
A Multiple Kernel Learning Approach for Human Behavioral Task Classification using STN-LFP Signal
Hosein M. Golshan, Adam O. Hebb, Sara J. Hanrahan +2
Deep Brain Stimulation (DBS) has gained increasing attention as an effective method to mitigate Parkinsons disease (PD) disorders. Existing DBS systems are open-loop such that the…
Facial Expression Recognition from World Wild Web
Ali Mollahosseini, Behzad Hassani, Michelle J. Salvador +3
Recognizing facial expression in a wild setting has remained a challenging task in computer vision. The World Wide Web is a good source of facial images which most of them are capt…