This article studies the continual learning task from the perspective of multimodal fusion. In the multimodal fusion problem, the unified representations of heterogeneous modalities are continuously updated, while the classifier is also constantly refreshed for each multimodal learning task. To tackle this point, we establish a continual learning framework for multimodal learning and design an effective online dictionary updating method. Finally, we experimentally verify a complex material identification task and obtain promising results.
No takes yet. Share an insight, caveat, or question.
Sun et al. (2020) studied this question.
Synapse has enriched 3 closely related papers on similar clinical questions. Consider them for comparative context: