no code implementations • 20 Oct 2023 • Irene Bonafonte, Cristina Bustos, Abraham Larrazolo, Gilberto Lorenzo Martinez Luna, Adolfo Guzman Arenas, Xavier Baro, Isaac Tourgeman, Mercedes Balcells, Agata Lapedriza
In this paper, we analyze the contribution of different passively collected sensor data types (WiFi, GPS, Social interaction, Phone Log, Physical Activity, Audio, and Academic features) to predict daily selfreport stress and PHQ-9 depression score.
1 code implementation • 18 Oct 2023 • Cristina Bustos, Carles Civit, Brian Du, Albert Sole-Ribalta, Agata Lapedriza
First, we test on WEBEmo and compare the CLIP-E architectures with state-of-the-art (SOTA) models and with CLIP Zero-Shot.
no code implementations • 3 Feb 2022 • Cristina Bustos, Daniel Rhoads, Agata Lapedriza, Javier Borge-Holthoefer, Albert Solé-Ribalta
In this paper, by considering historical accident data and Street View images, we detail how to automatically predict the impact (increase or decrease) of urban interventions on accident incidence.
no code implementations • 22 Oct 2021 • Cristina Bustos, Daniel Rhoads, Albert Sole-Ribalta, David Masip, Alex Arenas, Agata Lapedriza, Javier Borge-Holthoefer
At the moment, urban mobility research and governmental initiatives are mostly focused on motor-related issues, e. g. the problems of congestion and pollution.
no code implementations • 27 Sep 2021 • Cristina Bustos, Neska ElHaouij, Albert Sole-Ribalta, Javier Borge-Holthoefer, Agata Lapedriza, Rosalind Picard
Several studies have shown the relevance of biosignals in driver stress recognition.