Maria A. Zuluaga — accepted AI-conference papers

2023

StressID: a Multimodal Dataset for Stress Identification

Hava Chaptoukaev, Valeriya Strizhkova, Michele Panariello, Bianca Dalpaos, Aglind Reka, Valeria Manera +7

NeurIPS 2023poster

StressID is a new dataset specifically designed for stress identification from unimodal and multimodal data. It contains videos of facial expressions, audio recordings, and physiological signals. The video and audio recordings are acquired using an RGB camera with an integrated microphone. The physi…

Cited by 15 Source ↗PDF ↗code ↗Scholar ↗

2022

Exploring Auditory Acoustic Features for The Diagnosis of Covid-19

Madhu R. Kamble, Jose Patino, Maria A. Zuluaga, Massimiliano Todisco

ICASSP 2022accepted

The current outbreak of a coronavirus, has quickly escalated to become a serious global problem that has now been declared a Public Health Emergency of International Concern by the World Health Organization. Infectious diseases know no borders, so when it comes to controlling outbreaks, timing is ab…

Cited by 0 Source ↗Scholar ↗

2021

Maximum Roaming Multi-Task Learning

Lucas Pascal, Pietro Michiardi, Xavier Bost, Benoit Huet, Maria A. Zuluaga

AAAI 2021technical

Multi-task learning has gained popularity due to the advantages it provides with respect to resource usage and performance. Nonetheless, the joint optimization of parameters with respect to multiple tasks remains an active research topic. Sub-partitioning the parameters between different tasks has p…

Cited by 34 Source ↗PDF ↗code ↗Scholar ↗