Here’s something fun. Our hacker [Willow Cunningham] has sent us a copy of their homework. This is their final project for the “ECE 574: Cluster Computing” course at the University of Maine ...

Hence we proposes a semi-supervised retinal image classification method by a Hybrid Graph Convolutional Network (HGCN). This HGCN network designs a modularity-based graph learning module and ...

Endogenous intracellular allosteric modulators of GPCRs remain largely unexplored, with limited binding and phenotype data available. This gap arises from the lack of robust computational methods for ...

Here’s something fun. Our hacker [Willow Cunningham] has sent us a copy of their homework. This is their final project for the “ECE 574: Cluster Computing” course at the University of Maine ...

To explore the potential of large kernel convolution, we propose a hyperspectral image (HSI) classification algorithm in this paper that utilizes a large kernel convolution module combined with ...

In this paper, we propose a Hierarchical Aligned Subtree Convolutional Network (HA-SCN) for graph classification ... we define a novel subtree convolution and pooling operation that hierarchically ...

Levels of supply and demand for varying prices can be plotted on a graph as curves, and the intersection of these curves marks the equilibrium or market-clearing price at which demand equals ...

In this paper, we propose an end-to-end framework for EEG classification that integrates power spectral density (PSD) and visibility graph (VG) features together with deep learning (DL) techniques.