🔗 Bipartite Graph Classification using Graph Partitioning and Neural Networks This project explores the classification of bipartite graphs using deep learning methods. It combines classical graph ...

Specifically, to fully explore the characteristics of the spectral and spatial contexts in HSIs, we propose a novel superpixel and pixel coclustering framework with bipartite graph partitioning in the ...

Wang, H. (1999) On 2-Factors of a Bipartite Graph. Journal of Graph Theory, 31, 101-106.

Discover the groundbreaking algorithm solving Lozin's conjecture for bipartite Star123-free graphs, extending known classes of bipartite graphs.

Clustering large hyperspectral images (HSIs) is a very challenging problem because large HSIs have high dimensionality, large spectral variability, and large computational and memory consumption.

Graph Theory in computer Application. Features of Graph Theory project are: Bipartile, Planner, Tree, paths of 1,2,3,... n length, cycles (loops) of 3,4,,,,n length, Euler paths or cycles, Hamilton ...

Gallai–Ramsey theory lies at the intersection of graph colouring and Ramsey theory, providing a framework for understanding how structures emerge in edge-coloured graphs.