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Found 6 papers, 2 papers with code
Möbius Convolutions for Spherical CNNs
M\"obius transformations play an important role in both geometry and spherical image processing - they are the group of conformal automorphisms of 2D surfaces and the spherical equivalent of homographies.
Field Convolutions for Surface CNNs
We present a novel surface convolution operator acting on vector fields that is based on a simple observation: instead of combining neighboring features with respect to a single coordinate parameterization defined at a given point, we have every neighbor describe the position of the point within its own coordinate frame.
Efficient Spatially Adaptive Convolution and Correlation
Fast methods for convolution and correlation underlie a variety of applications in computer vision and graphics, including efficient filtering, analysis, and simulation.
A Community-Developed Open-Source Computational Ecosystem for Big Neuro Data
Big imaging data is becoming more prominent in brain sciences across spatiotemporal scales and phylogenies.
Neurons and Cognition Quantitative Methods
Automatic Annotation of Axoplasmic Reticula in Pursuit of Connectomes
The contribution of this work is the introduction of a straightforward and robust pipeline which annotates axoplasmic reticula with high precision, contributing towards advancements in automatic feature annotations in neural EM data.
Automatic Annotation of Axoplasmic Reticula in Pursuit of Connectomes using High-Resolution Neural EM Data
Accurately estimating the wiring diagram of a brain, known as a connectome, at an ultrastructure level is an open research problem.
