Author: msiplab

Posted on

Accepted by IEEE/IEIE ICCE-Asia 2020

The following research topic has been accepted by IEEE/IEIE ICCE-Asia @Seoul, Republic of Korea

Title: ‘Convolutional Nonlinear Dictionary with Cascaded Structure Filter Banks’
Authors: Ruiki Kobayashi and Shogo Muramatsu

The following tutorial is also planed.

Tutorial Title: Sparsity-Aware High-Dimensional Data Restoration with Convolutional Dictionary Learning
Lecturer: Shogo Muramatsu

The event was postponed from April to November due to the impact of COVID-19.

 

Posted on

APSIPA Distinguished Lecturer

I’ve been elected as an APSIPA Distinguished Lecturer for Term 2020-2021.

  • Title of Lecture: “Sparsity-Aware Image and Volumetric Data Restoration with Convolutional Dictionary Learning” etc.
  • Abstract: In this lecture, sparsity-aware restoration process of images and volumetric data is outlined. First, the purpose and application examples of image and volumetric data restoration are introduced. Then, the relationship between simultaneous equations and signal restoration is illustrated. The following topics are also summarized: Inner products and filtering, linear systems and matrices, filter banks and synthesis dictionaries, sparse modeling and MAP estimation, image generation and prior knowledge. Convolutional dictionary learning is also explained in connection with the design of parametric filter banks. Finally, the nonlinear extension of convolution dictionary is discussed and compared with convolutional neural networks (CNNs).
  • APSIPA – Education

Shogo MURAMATSU

Posted on

Presentation schedule after Aug. 2019

Internatinal Conference

  • Genki FUJII, Yuta YOSHIDA, Shogo MURAMATSU, Shunsuke ONO, Samuel CHOI, Takeru OTA, Fumiaki NIN, Hiroshi HIBINO: OCT Volumetric Data Restoration with Latent Distribution of Refractive Index, Proc. of 2019 IEEE International Conference on Image Processing (ICIP), Taipei, Sept. 2019, to appear
  • Weiwei SHAN, Shogo MURAMATSU, Akira OSHIMA and Hiroyoshi YAMADA: Successive Stripe Artifact Removal Based on Robust PCA for Millimeter Wave Automotive Radar Image, Proc. of APSIPA ASC 2019, Lanzhou,  Dec. 2019, to appear