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Found 3 papers, 1 papers with code
Transformer-Based Neural Surrogate for Link-Level Path Loss Prediction from Variable-Sized Maps
The transformer model attends to the regions that are relevant for path loss prediction and, therefore, scales efficiently to maps of different size.
How do Cross-View and Cross-Modal Alignment Affect Representations in Contrastive Learning?
Various state-of-the-art self-supervised visual representation learning approaches take advantage of data from multiple sensors by aligning the feature representations across views and/or modalities.
Hearing What You Cannot See: Acoustic Vehicle Detection Around Corners
A novel method is presented to classify if and from what direction a vehicle is approaching before it is visible, using as input Direction-of-Arrival features that can be efficiently computed from the streaming microphone array data.
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