Skip to content

can use graph cut to multi-label task in graph neural network? #2

@tanjia123456

Description

@tanjia123456

Hello, thanks of your contribution about such good work.
I am using graph neural network to parcel brain region, however the result is not good, I want to use graph cut as post process.
The inputs of my current model are: adjacency matrix (10242, 10242), feature matrix (10242, 6), label matrix (10242). The output is the probability y that each node belongs to a label, and its dimension is (10242, 36)
I want to use graph cut to update y for better performance.

I have a few questions about your code:
First, most of graph cut is only for two categories. Can you do multi label tasks?
Second, if I want to do post-processing, what should my input be?

Metadata

Metadata

Assignees

No one assigned

    Labels

    No labels
    No labels

    Projects

    No projects

    Milestone

    No milestone

    Relationships

    None yet

    Development

    No branches or pull requests

    Issue actions