Multimodal learning
Dnr:
NAISS 2024/22-112
Type:
NAISS Small Compute
Principal Investigator:
Selpi Selpi
Affiliation:
Chalmers tekniska högskola
Start Date:
2024-01-30
End Date:
2025-02-01
Primary Classification:
10201: Computer Sciences
Webpage:
Allocation
Abstract
In this project, we will investigate the impact of different ways of aligning and fusing multimodal data on the performance of a downstream task like object detection.