Sorry, this entry is only available in Japanese.
(日本語) IEICE ESS Fundamentals Review 4月号記事掲載
Presentation schedule after June 2021
International Conference
- Yusuke Arai, Shogo Muramatsu, Hiroyasu Yasuda, Kiyoshi Hayasaka, Yu Otake: Sparse-Coded Dynamic Mode Decomposition on Graph for Prediction of River Water Level Distribution, Proc. of 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , June 2021, to appear
- M Ibnul Morshed and Shogo Muramatsu: Improvement of Object Detection from SAR Image Using Speckle Filter, Proc. of ITC-CSCC2021, June 2021, to appear
- Jikai Li, Ruiki Kobayashi, Shogo Muramatsu and Gwanggil Jeon: Image Restoration with Structured Deep Image Prior, Proc. of ITC-CSCC2021, June 2021, to appear
- Dongqi Liu, Yutaka Naito, Chen Zhang, Shogo Muramatsu, Hiroyasu Yasuda, Kiyoshi Hayasaka and Yu Otake: River Flow Path Control with Reinforcement Learning, Proc. of 2021 IEEE International Conference on Autonomous Systems (ICAS), Aug. 2021, to appear
(日本語) 第35回信号処理シンポジウムのご報告
(日本語) IEEE/IEIE ICCE-Asia 2020@Busan のご報告
(日本語) サマーセミナー2020のご報告
Published SaivDr-Release20200903
We updated SaivDr (Sparsity-Aware Image and Volumetric Data Restoration) package for the first time in about six months.
New this time, we added custom layers and sample codes for use with MATLAB Deep Learning Toolbox. It allows for more flexible DAG configuration than before.
NSOLT enables you to realize Parseval tight, symmetric and multi-resolution convolutional layers, and you can place NSOLT as a convolutional layer in a corner of a convolutional neural network.

We hope you will give it a try.
Acknowledgments: This work was supported by KAKENHI JP19H04135.

