22 citations · 61 across the 7 of their papers we have counts for
7 papers
Pain level and pain-related behaviour classification using GRU-based sparsely-connected RNNs
Mohammad Mahdi Dehshibi, Temitayo Olugbade, Fernando Diaz-de-Maria +2
There is a growing body of studies on applying deep learning to biometrics analysis. Certain circumstances, however, could impair the objective measures and accuracy of the propose…
Bridging the gap between emotion and joint action
M. M. N. Bieńkiewicz, A. Smykovskyi, T. Olugbade +5
Our daily human life is filled with a myriad of joint action moments, be it children playing, adults working together (i.e., team sports), or strangers navigating through a crowd.…
Multimodal Data Fusion based on the Global Workspace Theory
Cong Bao, Zafeirios Fountas, Temitayo Olugbade +1
We propose a novel neural network architecture, named the Global Workspace Network (GWN), which addresses the challenge of dynamic and unspecified uncertainties in multimodal data…
EMOPAIN Challenge 2020: Multimodal Pain Evaluation from Facial and Bodily Expressions
Joy O. Egede, Siyang Song, Temitayo A. Olugbade +7
The EmoPain 2020 Challenge is the first international competition aimed at creating a uniform platform for the comparison of machine learning and multimedia processing methods of a…
Learning Bodily and Temporal Attention in Protective Movement Behavior Detection
Chongyang Wang, Min Peng, Temitayo A. Olugbade +3
For people with chronic pain, the assessment of protective behavior during physical functioning is essential to understand their subjective pain-related experiences (e.g., fear and…
Chronic-Pain Protective Behavior Detection with Deep Learning
Chongyang Wang, Temitayo A. Olugbade, Akhil Mathur +3
In chronic pain rehabilitation, physiotherapists adapt physical activity to patients' performance based on their expression of protective behavior, gradually exposing them to feare…