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Improving Hyperspectral Adversarial Robustness Under Multiple Attacks
Semantic segmentation models classifying hyperspectral images (HSI) are vulnerable to adversarial examples.
The Stanford Drone Dataset is More Complex than We Think: An Analysis of Key Characteristics
Our contributions include the outlining of key characteristics in the SDD, employment of an information-theoretic measure and custom metric to clearly visualize those characteristics, the implementation of the PECNet and Y-Net trajectory prediction models to demonstrate the outlined characteristics' impact on predictive performance, and lastly we provide a comparison between the SDD and Intersection Drone (inD) Dataset.
CEU-Net: Ensemble Semantic Segmentation of Hyperspectral Images Using Clustering
These approaches use patching to incorporate the rich neighborhood information in images and exploit the simplicity and segmentability of the most common HSI datasets.
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