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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| SIP, SP, EA, IPSJ-SLP [detail] | 2024-02-29 16:20 |
Okinawa | (Primary: On-site, Secondary: Online) |
 EA2023-77 SIP2023-124 SP2023-59 |
In this paper, we consider a dynamic sensor placement problem where sensors can move within a network over time. Sensor ... [more] | EA2023-77 SIP2023-124 SP2023-59 pp.97-102 |
| SIS | 2023-03-02 11:00 |
Chiba | Chiba Institute of Technology (Primary: On-site, Secondary: Online) |
Blink detection from one-dimensional face signal by using convolutional sparse dictionary learning Souichiro Maruyama, Makoto Nakashizuka (CIT) SIS2022-40 |
In this report, a blink detection method from average intensities of whole facial videos using convolutional dictionary... [more] | SIS2022-40 pp.1-4 |
| IE, ITS, ITE-AIT, ITE-ME, ITE-MMS [detail] | 2022-02-21 12:45 |
Online | Online | Quality Assessment for 3D CG Image Colorization Using Visible Digital Watermarking after Noise Removal Based on Sparse Dictionary Learning Coding Norifumi Kawabata (Hokkaido Univ.) |
Thus far, we discussed to represent image data whether it is possible or not to represent meaning image how requirement ... [more] | |
| EMM, IT | 2021-05-20 16:10 |
Online | Online | [Invited Talk]
Secure Computation of Sparse Modeling
-- Edge AI with Lightweight and Small Amounts of Data -- Takayuki Nakachi (Univ. of the Ryukyus) IT2021-6 EMM2021-6 |
With the advent of the big data, IoT, AI era, all digital contents continue to increase. Sparse modeling is drawing atte... [more] | IT2021-6 EMM2021-6 pp.31-36 |
| MI, IE, SIP, BioX, ITE-IST, ITE-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] | |
| NLP, NC (Joint) |
2020-01-24 11:10 |
Okinawa | Miyakojima Marine Terminal | Proposal of Compression Method for Planetary Surface Image using Sparse Coding Yoshifumi Uesaka, Hayaru Shouno (UEC) NC2019-65 |
In recent years, the demand for space development has been increasing. We treat an efficient image transmitting system f... [more] | NC2019-65 pp.33-38 |
| IMQ | 2019-10-04 14:00 |
Osaka | Osaka University | 3D CG Image Quality Assessment Including Noise Removal Based on Sparse Dictionary Learning Coding Norifumi Kawabata (Tokyo Univ. of Science) IMQ2019-6 |
By appearing of high-definition and high-quality images, it comes to increase many chance to process image big data. If ... [more] | IMQ2019-6 pp.1-10 |
| SIS, IPSJ-AVM, ITE-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) SIS2019-6 |
We propose a fast single super resolution which is comparable image quality with conventional methods without being bas... [more] | SIS2019-6 pp.29-34 |
| EMM | 2019-03-14 11:30 |
Okinawa | TBD | Image Patch Modeling using Secure Computation of Sparse Dictionary Learning Takayuki Nakachi (NTT), Hitoshi Kiya (Tokyo Metro. Univ.) EMM2018-115 |
With the advent of the big data era, digital content continues to increase. Sparse coding is attracting attention as an... [more] |
EMM2018-115 pp.129-134 |
| SIS | 2019-03-06 15:10 |
Tokyo | Tokyo Univ. Science, Katsushika Campus | Secure Computation of Sparse Dictionary Learning Takayuki Nakachi, Yukihiro Bandoh (NTT), Hitoshi Kiya (Tokyo Metro. Univ.) SIS2018-43 |
With the advent of the big data era, all digital contents continue to increase. Sparse modeling is drawing attention as ... [more] | SIS2018-43 pp.35-40 |
| NC, MBE (Joint) |
2019-03-06 15:50 |
Tokyo | University of Electro Communications | PET Image Reconstruction by use of Dictionary Learning Naohiro OKumura, Hayaru Shouno (UEC) NC2018-85 |
Nowadays, Positron Emission Tomography (PET) scan is focused in the field of pathological diagnosis.In order to obtain a... [more] | NC2018-85 pp.221-226 |
| ITS, IE, ITE-MMS, ITE-HI, ITE-ME, ITE-AIT [detail] | 2019-02-20 14:45 |
Hokkaido | Hokkaido Univ. | Encrypted Image Classification by Using Secure OMP Computation Takayuki Nakachi (NTT), Hitoshi Kiya (Tokyo Metro. Univ.) ITS2018-84 IE2018-105 |
Currently, huge amounts of image/video are being recorded and uploaded every day by surveillance systems or SNS services... [more] | ITS2018-84 IE2018-105 pp.227-232 |
| IBISML | 2016-03-18 11:05 |
Tokyo | Institute of Statistical Mathematics | Block-sparse Extensions of Recovery Conditions of Overcomplete Dictionaries Yasushi Terazono, Kenji Yamanishi (UTokyo) IBISML2015-101 |
In overcomplete dictionary learning problems, observed data are modeled as products of overcomplete dictionaries and spa... [more] | IBISML2015-101 pp.55-58 |
| SP, IPSJ-MUS | 2014-05-25 11:30 |
Tokyo | A joint restricted Boltzmann machine for dictionary learning in sparse-representation-based voice conversion Toru Nakashika, Tetsuya Takiguchi, Yasuo Ariki (Kobe Univ.) SP2014-34 |
In voice conversion, sparse-representation-based methods have recently been garnering attention because they are, relati... [more] | SP2014-34 pp.343-348 |
|
| SIP, CAS, CS | 2013-03-14 14:40 |
Yamagata | Keio Univ. Tsuruoka Campus (Yamagata) | Self-learning super resolution by L2-norm Daiki Azuma (Keio Univ.), Kazu Mishiba (Tottori Univ.), Masaaki Ikehara (Keio Univ.) CAS2012-106 SIP2012-137 CS2012-112 |
In this paper, we propose a single image super resolution technique by L2 approximation without any training. Recently i... [more] | CAS2012-106 SIP2012-137 CS2012-112 pp.57-61 |
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