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20122023
most citedSemi-Supervised Classification with Graph Convolutional Networks

8.1k citations · 11.6k across the 65 of their papers we have counts for

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Showing 2018 · cs.CVShow all

5 papers · 2 filters

cs.CV2018

Graph Refinement based Airway Extraction using Mean-Field Networks and Graph Neural Networks

Raghavendra Selvan, Thomas Kipf, Max Welling +4

Graph refinement, or the task of obtaining subgraphs of interest from over-complete graphs, can have many varied applications. In this work, we extract trees or collection of sub-t…

cs.CV2018

Sample Efficient Semantic Segmentation using Rotation Equivariant Convolutional Networks

Jasper Linmans, Jim Winkens, Bastiaan S. Veeling +2

We propose a semantic segmentation model that exploits rotation and reflection symmetries. We demonstrate significant gains in sample efficiency due to increased weight sharing, as…

cs.CV2018

Rotation Equivariant CNNs for Digital Pathology

Bastiaan S. Veeling, Jasper Linmans, Jim Winkens +2

We propose a new model for digital pathology segmentation, based on the observation that histopathology images are inherently symmetric under rotation and reflection. Utilizing rec…

cs.CV2018

Extraction of Airways using Graph Neural Networks

Raghavendra Selvan, Thomas Kipf, Max Welling +3

We present extraction of tree structures, such as airways, from image data as a graph refinement task. To this end, we propose a graph auto-encoder model that uses an encoder based…

cs.CV2018

Mean Field Network based Graph Refinement with application to Airway Tree Extraction

Raghavendra Selvan, Max Welling, Jesper H. Pedersen +2

We present tree extraction in 3D images as a graph refinement task, of obtaining a subgraph from an over-complete input graph. To this end, we formulate an approximate Bayesian inf…