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Found 2 papers, 1 papers with code
Learning Interpretable Microscopic Features of Tumor by Multi-task Adversarial CNNs To Improve Generalization
Here we show that our architecture, by learning end-to-end an uncertainty-based weighting combination of multi-task and adversarial losses, is encouraged to focus on pathology features such as density and pleomorphism of nuclei, e. g. variations in size and appearance, while discarding misleading features such as staining differences.
DeepFloat: Resource-Efficient Dynamic Management of Vehicular Floating Content
Opportunistic communications are expected to playa crucial role in enabling context-aware vehicular services.
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