Results 91 to 100 of about 2,513,053 (383)
Emotion Recognition in the Wild using Deep Neural Networks and Bayesian Classifiers
, 2017 Group emotion recognition in the wild is a challenging problem, due to the unstructured environments in which everyday life pictures are taken. Some of the obstacles for an effective classification are occlusions, variable lighting conditions, and image ...
Cangelosi, Angelo +4 more
core +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT C‐truncating variants in the charged multivesicular body protein 2B (CHMP2B) gene are a rare cause of frontotemporal lobar degeneration (FTLD), previously identified only in Denmark, Belgium, and China. We report a novel CHMP2B splice‐site variant (c.35‐1G>A) associated with familial FTLD in Spain. The cases were two monozygotic male twins who
Sara Rubio‐Guerra +17 more
wiley +1 more source
EEG-Based Emotion Recognition Using Regularized Graph Neural Networks [PDF]
IEEE Transactions on Affective Computing, 2019 Electroencephalography (EEG) measures the neuronal activities in different brain regions via electrodes. Many existing studies on EEG-based emotion recognition do not fully exploit the topology of EEG channels.
Peixiang Zhong, Di Wang, C. Miao
semanticscholar +1 more source
A Comprehensive Review of Speech Emotion Recognition Systems
IEEE Access, 2021 During the last decade, Speech Emotion Recognition (SER) has emerged as an integral component within Human-computer Interaction (HCI) and other high-end speech processing systems.
T. Wani +4 more
semanticscholar +1 more source
Progressive Neural Networks for Transfer Learning in Emotion Recognition
, 2017 Many paralinguistic tasks are closely related and thus representations learned in one domain can be leveraged for another. In this paper, we investigate how knowledge can be transferred between three paralinguistic tasks: speaker, emotion, and gender ...
Aldeneh, Zakaria +4 more
core +1 more source
Emotion Recognition by Physiological Signals
Electronic Imaging, 2016 Recently, User’s effective state automatic recognition has become a popular research area. It has many applications ranging from health, education, and personalization. In this paper, emotional state arousal and valence induced by watching video clips are identified by physiological and electroencephalogram (EEG) signals by .
Ryan Gibson +5 more
openaire +3 more sources
Cerebello‐Prefrontal Connectivity Underlying Cognitive Dysfunction in Spinocerebellar Ataxia Type 2
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Spinocerebellar ataxia type 2 (SCA2) is a hereditary cerebellar degenerative disorder, with motor and cognitive symptoms. The constellation of cognitive symptoms due to cerebellar degeneration is named cerebellar cognitive affective syndrome (CCAS), which has increasingly been recognized to profoundly impact patients' quality of life;
Ami Kumar +7 more
wiley +1 more source
Recognition of Emotion Intensities Using Machine Learning Algorithms: A Comparative Study
Sensors, 2019 Over the past two decades, automatic facial emotion recognition has received enormous attention. This is due to the increase in the need for behavioral biometric systems and human–machine interaction where the facial emotion recognition and the ...
Dhwani Mehta +2 more
doaj +1 more source
Emotion recognition based on group phase locking value using convolutional neural network
Scientific Reports, 2023 Electroencephalography (EEG)-based emotion recognition is an important technology for human–computer interactions. In the field of neuromarketing, emotion recognition based on group EEG can be used to analyze the emotional states of multiple users ...
Gaochao Cui, Xueyuan Li, Hideaki Touyama
doaj +1 more source