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Overall, the studies reviewed here suggest that VAEs can serve as parts of larger systems, where they provide structured representations and help handle missing modalities.
TrajFusionNet+, a novel transformer-based model for pedestrian crossing intention prediction that combines sequential and visual representations of pedestrian trajectory with a graph-based representation of the scene context in order to predict pedestrian crossing intention, is introduced.
MultiCardioNet, a multimodal deep learning framework for early prediction of a composite ICU deterioration endpoint using MIMIC-IV data, suggests that the three modalities provide complementary information for this composite deterioration endpoint in the internal test setting.
It is demonstrated that task-guided style transfer can improve cross-domain coastal boundary segmentation while maintaining a static segmentation model, making it a promising approach for long-term coastal monitoring across heterogeneous remote sensing datasets.
Overall, the reviewed literature demonstrates that generative AI has substantial potential to improve brain MRI analysis through realistic data generation, enhanced image quality, and more informative feature representations.
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