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Found 5 papers, 2 papers with code
Is the U-Net Directional-Relationship Aware?
CNNs are often assumed to be capable of using contextual information about distinct objects (such as their directional relations) inside their receptive field.
Template-Based Graph Clustering
We propose a novel graph clustering method guided by additional information on the underlying structure of the clusters (or communities).
Approximation of dilation-based spatial relations to add structural constraints in neural networks
Several relations can be modeled as a morphological dilation of a reference object with a structuring element representing the semantics of the relation, from which the degree of satisfaction of the relation between another object and the reference object can be derived.
A Structural Graph-Based Method for MRI Analysis
Therefore, the development of a robust technique to aid in pediatric MRI analysis is necessary.
An incremental linear-time learning algorithm for the Optimum-Path Forest classifier
We present a classification method with incremental capabilities based on the Optimum-Path Forest classifier (OPF).
