Deep learning reveals nanoparticle shape from routine tracking analysis without new hardware

Researchers at the University of Tokyo and the Innovation Center of NanoMedicine (iCONM) have developed an artificial ...
IEEE

DAHBM-GCN: A Flexible Graph Convolution Network Accelerator With Multiple Dataflows and HBM

Abstract: Graph-structured data has been widely applied in transportation, molecular, and e-commerce networks, etc. Graph Convolutional Network (GCN) has emerged as an efficient approach to processing ...
IEEE

Integrating Fuzzy Clustering and Graph Convolution Network to Accurately Identify Clusters From Attributed Graph

Abstract: Attributed graph clustering is of significance for an in-depth understanding of the intrinsic organization of complex networks. Recently, owing to the powerful learning capability of deep ...