61 citations · 62 across the 2 of their papers we have counts for
7 papers
AudVowelConsNet: A Phoneme-Level Based Deep CNN Architecture for Clinical Depression Diagnosis
Muhammad Muzammel, Hanan Salam, Yann Hoffmann +2
Depression is a common and serious mood disorder that negatively affects the patient's capacity of functioning normally in daily tasks. Speech is proven to be a vigorous tool in de…
EEG based Major Depressive disorder and Bipolar disorder detection using Neural Networks: A review
Sana Yasin, Syed Asad Hussain, Sinem Aslan +3
Mental disorders represent critical public health challenges as they are leading contributors to the global burden of disease and intensely influence social and financial welfare o…
Deep Multi-Facial Patches Aggregation Network For Facial Expression Recognition
Ahmed Rachid Hazourli, Amine Djeghri, Hanan Salam +1
In this paper, we propose an approach for Facial Expressions Recognition (FER) based on a deep multi-facial patches aggregation network. Deep features are learned from facial patch…
Towards Robust Deep Neural Networks for Affect and Depression Recognition from Speech
Alice Othmani, Daoud Kadoch, Kamil Bentounes +3
Intelligent monitoring systems and affective computing applications have emerged in recent years to enhance healthcare. Examples of these applications include assessment of affecti…
Deep Multi-Facial patches Aggregation Network for Expression Classification from Face Images
Amine Djerghri, Ahmed Rachid Hazourli, Alice Othmani
Emotional Intelligence in Human-Computer Interaction has attracted increasing attention from researchers in multidisciplinary research fields including psychology, computer vision,…
MFCC-based Recurrent Neural Network for Automatic Clinical Depression Recognition and Assessment from Speech
Emna Rejaibi, Ali Komaty, Fabrice Meriaudeau +2
Clinical depression or Major Depressive Disorder (MDD) is a common and serious medical illness. In this paper, a deep recurrent neural network-based framework is presented to detec…