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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| ITE-ME, ITE-IST, BioX, SIP, MI, IE [detail] | 2024-06-06 13:10 |
Niigata | Nigata University (Ekinan-Campus "TOKIMATE") (Niigata) | 3-Way Locally-Structured Unitary Network for Volumetric Data Processing Miyu Maruyama, Yasas Godage, Shogo Muramatsu (Niigata Univ.) |
This work proposes a 3-Way Locally Structured Unitary Network (3-Way LSUN) as a volumetric data analysis method. With ad... [more] | |
| CNR | 2023-08-09 14:45 |
Hokkaido | (Hokkaido, Online) (Primary: On-site, Secondary: Online) |
Construction of Groynes Reconfiguration System for Elucidation of River Channel Change Mechanism Chen Zhang, Yuki Takahashi, Daichi Moteki, Hiroyasu Yasuda, Kiyoshi Hayasaka, Shogo Muramatsu (Niigata Univ.)  CNR2023-4 |
In this report, a new actuation method is proposed for improving the prototype of our proposed river cyber-physical syst... [more] | CNR2023-4 pp.18-21 |
| SP, IPSJ-SLP, EA, SIP [detail] | 2023-03-01 16:10 |
Okinawa | (Okinawa, Online) (Primary: On-site, Secondary: Online) |
On Design of Real Filters For Directed Graph Signals Shogo Muramatsu, Hotaka Kitamura, Hiroyashu Yasuda (Niigta Univ.), Yuichi Tanaka (Osaka Univ.) EA2022-124 SIP2022-168 SP2022-88 |
This study investigates a real-valued filter realization for directed graph signals. The authors proposed a para-graph F... [more] | EA2022-124 SIP2022-168 SP2022-88 pp.282-287 |
| SP, IPSJ-SLP, EA, SIP [detail] | 2023-03-01 16:30 |
Okinawa | (Okinawa, Online) (Primary: On-site, Secondary: Online) |
Low-bit Image Restoration with Loop-unrolled ISTA Shu Abe, Soushi Takahashi, Shogo Muramatsu (Niigata Univ) EA2022-125 SIP2022-169 SP2022-89 |
This study proposes a low-bit image restoration method based on a loop-unrolled network of Iterative Shrinkage Threshold... [more] | EA2022-125 SIP2022-169 SP2022-89 pp.288-293 |
| SIP | 2022-08-25 14:15 |
Okinawa | Nobumoto Ohama Memorial Hall (Ishigaki Island) (Okinawa, Online) (Primary: On-site, Secondary: Online) |
Multiresolution Convolutional-Sparse-Coded Dynamic Mode Decomposition and Its Application to Riverbed State Estimation Eisuke Kobayashi, Shogo Muramatsu, Hiroyasu Yasuda, Kiyoshi Hayasaka (Niigata Univ.) SIP2022-54 |
In this report, we propose a method that incorporates multi-resolution representation into Convolutional-Sparse-Coded Dy... [more] | SIP2022-54 pp.25-30 |
| SIP | 2022-08-25 14:33 |
Okinawa | Nobumoto Ohama Memorial Hall (Ishigaki Island) (Okinawa, Online) (Primary: On-site, Secondary: Online) |
Structured Deep Image Prior with Interscale Thresholding Jikai Li, Shogo Muramatsu (Niigata Univ.) SIP2022-55 |
This work proposes a novel image denoising technique inspired by the deep image prior (DIP) method. Our contribution is ... [more] | SIP2022-55 pp.31-36 |
| SIP | 2022-08-26 15:33 |
Okinawa | Nobumoto Ohama Memorial Hall (Ishigaki Island) (Okinawa, Online) (Primary: On-site, Secondary: Online) |
Locally-Structured Unitary Network to Capture Tangent Spaces of Manifold Godage Yasas, Shogo Muramatsu (Niigata Univ.) SIP2022-75 |
This work proposes a unique linear transform, locally-structured unitary network (LSUN), that captures tangent spaces of... [more] | SIP2022-75 pp.129-133 |
| SIP | 2022-08-26 15:51 |
Okinawa | Nobumoto Ohama Memorial Hall (Ishigaki Island) (Okinawa, Online) (Primary: On-site, Secondary: Online) |
Design of Structured Convolutional Dictionary by Manifold Optimization for Image Restoration Soushi Takahashi, Shogo Muramatsu (Niigata Univ.) SIP2022-76 |
This work reports on the effectiveness of a structured convolutional dictionary learning that introduces manifold optimi... [more] | SIP2022-76 pp.134-139 |
| IE, SIP, BioX, ITE-IST, ITE-ME [detail] | 2021-06-04 14:45 |
Online | Online (Online) | Acceleration of High-Dimensional Signal Restoration with Primal-Dual Splitting Gai Yamamoto, Shogo Muramatsu (Niigata Univ.) |
[more] | |
| IE, SIP, BioX, ITE-IST, ITE-ME [detail] | 2021-06-04 15:15 |
Online | Online (Online) | Acceleration of Dictionary Learning by Non-Separable Oversampled Lapped Transform for Image Restoration Soushi Takahashi, Shogo Muramatsu (Niigata Univ.) |
[more] | |
| SANE | 2020-06-26 14:30 |
Online | Online (Online) | Fundamental study on human motion classification with millimeter wave FM-CW radar by using CNN Fumiya Sakagami, Hiroyoshi Yamada, Shogo Muramatsu (Niigata Univ.) SANE2020-12 |
[more] | SANE2020-12 pp.19-24 |
| MSS, CAS, SIP, VLD | 2020-06-18 15:00 |
Online | Online (Online) | [Panel Discussion]
The role of System and Signal Processing Subsociety
-- Pros & Cons of Online Video Meeting -- Shogo Muramatsu (Niigata Univ.), Shigemasa Takai (Osaka Univ.), Yasuhiro Takashima (Univ. of Kitakyushu), Kasunori Hayashi (Kyoto Univ.), Daisuke Fukuda (Fujitsu Lab.) CAS2020-10 VLD2020-10 SIP2020-26 MSS2020-10 |
The four technical committees (TCs) of Systems and Signal Processing sub-society, i.e., TCs of Circuits and Systems (CAS... [more] | CAS2020-10 VLD2020-10 SIP2020-26 MSS2020-10 pp.53-56 |
| MI, IE, SIP, BioX, ITE-IST, ITE-ME [detail] | 2020-05-28 10:50 |
Online | 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] | |
| SP, EA, SIP | 2020-03-03 09:00 |
Okinawa | Okinawa Industry Support Center (Okinawa) (Cancelled but technical report was issued) |
[Poster Presentation]
Performance Evaluation of Convolutional-Sparse-Coded Dynamic Mode Decomposition in River Groynes Model Experiment Yusuke Arai, Yuhei Kaneko, Shogo Muramatsu, Hiroyasu Yasuda, Kiyoshi Hayasaka, Yu Otake (Niigata Univ.) EA2019-154 SIP2019-156 SP2019-103 |
[more] | EA2019-154 SIP2019-156 SP2019-103 pp.307-312 |
| SANE | 2019-11-28 14:00 |
Osaka | OIT UMEDA Campus (Osaka) | Fundamental Study on Side Targets Detection for Automotive Millimeter-Wave SAR Imaging in Curved Tracks Akira Oshima, Hiroyoshi Yamada, Shogo Muramatsu (Niigata Univ.) SANE2019-70 |
In recently, automatic operating system for vehicle, such as advanced driver assistance system, has been intensively stu... [more] | SANE2019-70 pp.1-4 |
| SIP, MI, IE | 2019-05-23 13:25 |
Aichi | (Aichi) | OCT Volumetric Data Restoration with 3-D Non-separable Oversampled Lapped Transforms Yuta Yoshida, Genki fujii (Graduate School of Science and Tech., Niigata Univ.), Shogo Muramatsu, Samuel Choi (Niigata Univ.), Shunsuke Ono (Tokyo Institute of Tech.), Takeru Ota, Fumiaki Nin, Hiroshi Hibino (Niigata Univ.) SIP2019-2 IE2019-2 MI2019-2 |
[more] | SIP2019-2 IE2019-2 MI2019-2 pp.7-12 |
| SANE | 2018-10-12 13:55 |
Tokyo | The University of Electro-Communications (Tokyo) | Fundamental Study on Ambiguity Suppression by Using SIMO radar of Automotive Squint-mode MW-SAR Akira Oshima, Hiroyoshi Yamada, Shogo Muramatsu, Yoshio Yamaguchi (Niigata Univ.) SANE2018-52 |
Automatic operating system for vehicle, such as advanced driver assistance system, has been intensively studied recently... [more] | SANE2018-52 pp.45-49 |
| SIP | 2018-08-20 14:25 |
Tokyo | Takushoku Univ. Bunkyo Campus. (Tokyo) | Experiment on OCT Volumetric Data Restoration via Hierarchical Sparsity and Hard Constraint Genki Fujii, Shogo Muramatsu, Samuel Choi (Niigata Univ.), Shunsuke Ono (Tokyo Tech.), Takeru Ota, Fumiaki Nin, Hiroshi Hibino (Niigata Univ.) SIP2018-58 |
In this report, we try to apply the restoration algorithm proposed in [1] to real observation data acquired byoptical co... [more] | SIP2018-58 pp.7-12 |
| SIP | 2018-08-20 15:15 |
Tokyo | Takushoku Univ. Bunkyo Campus. (Tokyo) | River Data Analysis by Dynamic Mode Decomposition Kyohei Igo, Shogo Muramatsu, Hiroyasu Yasuda, Kiyoshi Hayasaka (Niigata Univ.), Gene Cheung (NII) SIP2018-60 |
[more] | SIP2018-60 pp.19-24 |
| SIP | 2018-08-21 09:15 |
Tokyo | Takushoku Univ. Bunkyo Campus. (Tokyo) | On Structural Constraint for Convolutional Layers in CNN Shota Kayamori, Shogo Muramatsu (Niigata Univ.) SIP2018-63 |
This work investigates Convolutional Neural Network (CNN) constituted by convolution layers imposed structural constrain... [more] | SIP2018-63 pp.33-36 |
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