Deep Learning–Based Multimodal Data Fusion: Case Study in Food Intake Episodes Detection Using Wearable Sensors

Abstract

To conclude, the proposed fusion technique provides the possibility of embedding joint variability information over different modalities in just a single 2D representation which results in obtaining a more global view of different aspects of daily human activities at hand, and yet preserving the desired performance level in activity recognition.