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All Technical Committee Conferences (Searched in: All Years)
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| Search Results: Conference Papers |
| Conference Papers (Available on Advance Programs) (Sort by: Date Descending) |
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| Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
| IST, ME, IEICE-IE, IEICE-SIP, IEICE-BioX [detail] |
2021-06-04
15:15 |
Online |
Online |
Acceleration of Dictionary Learning by Non-Separable Oversampled Lapped Transform for Image Restoration
Soushi Takahashi, Shogo Muramatsu (Niigata Univ.) |
This study proposes to accelerate example-based design of non-separable oversampled lapped transform (NSOLT) for image r... [more] |
IST2021-27 ME2021-58
pp.87-92 |
| IEICE-MI, IEICE-IE, IEICE-SIP, IEICE-BioX, IST, ME [detail] |
2020-05-28
10:50 |
Online |
Online |
[Special Talk]
High-dimensional Signal Restoration by Convolutional Networks Driving Fusion Across Multiple Disciplines
-- Sparse Modeling and Convolutional Dictionary Learning --
Shogo Muramatsu (Niigata Univ.) |
This talk outlines a restoration process of high-dimensional signals such as image and volumetric data. With the develop... [more] |
IST2020-30 ME2020-81
p.13 |
| ME |
2020-02-08
12:15 |
Kanagawa |
Kanto Gakuin University |
Extension of blind image restoration using sparse optimization to multispectral images
Dan Suto, Yoshitaka Izumi, Souta Kawakami, Hiroyuki Kudo (Tsukuba Univ.) |
Blind image restoration is a method of restoring a clear image only from an image that has deteriorated due to defocus o... [more] |
ME2020-8
pp.23-26 |
| IEICE-SIS, IPSJ-AVM, 3DMT [detail] |
2019-06-13
14:25 |
Nagasaki |
Fukue Culture Center |
Single Image Super-Resolution for being flexible to downsampling kernel by using self-examplers
Shogo Seta, Takuro Yamaguchi, Masaaki Ikehara (Keio Univ) |
We propose a fast single super resolution which is comparable image quality with conventional methods without being bas... [more] |
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| IEICE-SIS, IPSJ-AVM, 3DMT [detail] |
2019-06-13
16:25 |
Nagasaki |
Fukue Culture Center |
[Invited Talk]
Sparse/low-rank Modeling for Image Processing
Seisuke Kyochi (The Univ. of Kitakyushu) |
This paper presents fundamental tools for image recovery by convex optimization and introduces some case study from the ... [more] |
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