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Found 2 papers, 1 papers with code
S4: Self-Supervised Sensing Across the Spectrum
We propose S4 a new self-supervised pre-training approach that significantly reduces the requirement for labeled training data by utilizing two new insights: (a) Satellites capture images in different parts of the spectrum such as radio frequencies, and visible frequencies.
Provable Defense Against Geometric Transformations
Geometric image transformations that arise in the real world, such as scaling and rotation, have been shown to easily deceive deep neural networks (DNNs).
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