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Masatoshi Nagahama

2 accepted papers

2022

Multimodal Graph Signal Denoising Via Twofold Graph Smoothness Regularization with Deep Algorithm Unrolling

ICASSP 2022accepted

We propose a denoising method of multimodal graph signals with twofold smoothness regularization. Graph signal processing assumes that a signal has an underlying structure that is represented by a graph. In each node of the graph, we often have multimodal data or features that are correlated across…

Cited by 0SourceScholar
2021

Graph Signal Denoising Using Nested-Structured Deep Algorithm Unrolling

ICASSP 2021accepted

In this paper, we propose a deep algorithm unrolling (DAU) based on a variant of the alternating direction method of multiplier (ADMM) called Plug-and-Play ADMM (PnP-ADMM) for denoising of signals on graphs. DAU is a trainable deep architecture realized by unrolling iterations of an existing optimiz…

Cited by 0SourceScholar