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Improving GNNs for Image Classification: Addressing Homophily Challenges

Graph Neural Networks (GNNs) are rapidly becoming essential tools in deep learning, but their effectiveness when applied to images is often limited by challenges in graph representation. Traditional image-to-graph conversions often result in structures with low homophily (dissimilar connected nodes)...

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Principais autores: Aryan Singh, Ciaran Eising, Patrick Denny, Pepijn van de Ven
Format: Artigo
Sprog:Inglês
Udgivet: IEEE 2025-01-01
Serier:IEEE Open Journal of the Computer Society
Fag:
Computer vision
Graph Neural Networks (GNNs)
classification
Online adgang:https://ieeexplore.ieee.org/document/11195142/
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