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Facial Recognition

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Deep Joint Spatiotemporal Network (DJSTN) for Efficient Facial Expression Recognition.

Sensors (Basel, Switzerland)
Understanding a person's feelings is a very important process for the affective computing. People express their emotions in various ways. Among them, facial expression is the most effective way to present human emotional status. We propose efficient ...

Dilated Skip Convolution for Facial Landmark Detection.

Sensors (Basel, Switzerland)
Facial landmark detection has gained enormous interest for face-related applications due to its success in facial analysis tasks such as facial recognition, cartoon generation, face tracking and facial expression analysis. Many studies have been prop...

A Multi-Column CNN Model for Emotion Recognition from EEG Signals.

Sensors (Basel, Switzerland)
We present a multi-column CNN-based model for emotion recognition from EEG signals. Recently, a deep neural network is widely employed for extracting features and recognizing emotions from various biosignals including EEG signals. A decision from a s...

Convergent evolution of face spaces across human face-selective neuronal groups and deep convolutional networks.

Nature communications
The discovery that deep convolutional neural networks (DCNNs) achieve human performance in realistic tasks offers fresh opportunities for linking neuronal tuning properties to such tasks. Here we show that the face-space geometry, revealed through pa...

On the use of Action Units and fuzzy explanatory models for facial expression recognition.

PloS one
Facial expression recognition is related to the automatic identification of affective states of a subject by computational means. Facial expression recognition is used for many applications, such as security, human-computer interaction, driver safety...

Deep Learning: The Good, the Bad, and the Ugly.

Annual review of vision science
Artificial vision has often been described as one of the key remaining challenges to be solved before machines can act intelligently. Recent developments in a branch of machine learning known as deep learning have catalyzed impressive gains in machin...

Branched convolutional neural networks incorporated with Jacobian deep regression for facial landmark detection.

Neural networks : the official journal of the International Neural Network Society
Facial landmark detection is to localize multiple facial key-points for a given facial image. While many methods have achieved remarkable performance in recent years, the accuracy remains unsatisfactory due to some uncontrolled conditions such as occ...

Predicting anxiety from wholebrain activity patterns to emotional faces in young adults: a machine learning approach.

NeuroImage. Clinical
BACKGROUND: It is becoming increasingly clear that pathophysiological processes underlying psychiatric disorders categories are heterogeneous on many levels, including symptoms, disease course, comorbidity and biological underpinnings. This heterogen...

Emotional arousal amplifies competitions across goal-relevant representation: A neurocomputational framework.

Cognition
Emotional arousal often facilitates memory for some aspects of an event while impairing memory for other aspects of the same event. Across three experiments, we found that emotional arousal amplifies competition among goal-relevant representations, s...

Cyborg groups enhance face recognition in crowded environments.

PloS one
Recognizing a person in a crowded environment is a challenging, yet critical, visual-search task for both humans and machine-vision algorithms. This paper explores the possibility of combining a residual neural network (ResNet), brain-computer interf...