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Helmholtz-Decomposition and Optical Flow: A new method to characterize GCamP recordings
To enable quantitative means of analysis and examine the structure of such prototypical events we propose a novel approach for the characterization of slow waves: The Helmholtz-Decomposition of gradient-based Dense Optical Flow of the pixeldense GCamP contrast (df/f).
A differentiable Gaussian Prototype Layer for explainable Segmentation
We introduce a Gaussian Prototype Layer for gradient-based prototype learning and demonstrate two novel network architectures for explainable segmentation one of which relies on region proposals.
But that's not why: Inference adjustment by interactive prototype revision
It shows that even correct classifications can rely on unreasonable prototypes that result from confounding variables in a dataset.
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