Frontiers

Multi-Scale graph wavelet convolutional network for hyperspectral image classification

Hyperspectral images (HSIs) have very high dimensionality and typically lack sufficient labeled samples, which significantly challenges their processing and analysis. These challenges contribute to ...
Frontiers

Weight-aware semi-supervised self-ensembling framework for interior decoration style ...

Automatic classification of interior decoration styles has great potential to guide and streamline the design process. Despite recent advancements, it remains challenging to construct an accurate ...
Scientific Research Publishing

Kipf, T.N. and Welling, M. (2016) Semi-Supervised Classification with Graph Convolutional ...

ABSTRACT: The rapid advancements in large language models (LLMs) have led to an exponential increase in survey papers, making it challenging to systematically track and analyze their evolving taxonomy ...
IEEE

Semi-Supervised Learning With Graph Learning-Convolutional Networks

Abstract: Graph Convolutional Neural Networks (graph CNNs) have been widely used for graph data representation and semi-supervised learning tasks. However, existing graph CNNs generally use a fixed ...
Scientific Research Publishing

Semi-Supervised Stochastic Configuration Networks Based on Manifold Regularization Framework ()

1 School of Mathematics and Statistics, Guilin University of Technology, Guilin, China. 2 Guangxi Colleges and Universities Key Laboratory of Applied Statistics, Guilin, China. The stochastic ...