Sorry, this entry is only available in Japanese.
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.
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