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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| RCC, ISEC, IT, WBS | 2024-03-13 14:40 |
Osaka | Osaka Univ. (Suita Campus) | Sparse Superposition Codes Using Second Order Reed-Muller: Orthogonal Encoding Tsukasa Osaka (Doshisha Univ.), Guanghui Song (Xidian Univ.), Tomotaka Kimura, Jun Cheng (Doshisha Univ.)  IT2023-92 ISEC2023-91 WBS2023-80 RCC2023-74 |
A family of block orthogonal sparse superposition codes is proposed. The dictionary matrix consists of all the second o... [more] |
IT2023-92 ISEC2023-91 WBS2023-80 RCC2023-74 pp.108-113 |
| EMM | 2024-03-02 14:00 |
Overseas | Day1:JEJU TECHNOPARK, Day2:JEJU Business Agency | [Poster Presentation]
Classification of AI generated images by sparse coding Daishi Tanaka, Michiharu Niimi (KIT) EMM2023-89 |
In recent years, advancements in generative AI technologies have made it increasingly challenging for human vision to di... [more] | EMM2023-89 pp.1-6 |
| 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 |
| EMM | 2023-01-26 13:35 |
Miyagi | Tohoku Univ. (Primary: On-site, Secondary: Online) |
Audio zero-watermarking method based on auditory spectral representation Atsuki Ichikawa, Masashi Unoki (JAIST) EMM2022-65 |
Audio zero-watermark technique creates a detection key from watermark and binary pattern generated from features of the ... [more] | EMM2022-65 pp.20-25 |
| 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 | 2022-01-27 14:35 |
Online | Online | Auditory Representation of Speech Signals Using a Matching Pursuit Algorithm and Sparse Coding Dung Kim Tran, Masashi Unoki (JAIST) EMM2021-87 |
Speech signals are the natural carrier of information such as linguistic, speaker individuality, and emotions, etc. Ther... [more] | EMM2021-87 pp.19-24 |
| NC, MBE (Joint) |
2021-03-04 09:50 |
Online | Online | Evaluation of effect of source noise on magnetoencephalography source estimation using a structured sparse model Kai Miyazaki, Shun Nirasawa, Kazuaki Akamatsu, Yoichi Miyawaki (UEC) NC2020-56 |
Magnetoencephalography (MEG) is a method to acquire human brain activity at a high temporal resolution, but its spatial ... [more] | NC2020-56 pp.77-82 |
| IT | 2020-12-03 13:40 |
Online | Online | Downlink Non-Orthogonal Multiple Access (NOMA) Using sparse superposition codes Hayato Tachiwana, Yutaka Jitsumatsu (Kyushu Univ.) IT2020-54 |
Non-orthogonal multiple access (NOMA) is considered to be a most promising next generation mobile communication systems.... [more] | IT2020-54 pp.159-164 |
| SIS, ITE-BCT | 2020-10-01 15:10 |
Online | Online | Fast Beamforming using Sparse Coding for mmWave Communications Yitu Wang, Takayuki Nakachi (NTT Lab) SIS2020-19 |
The sensitivity of mmWave to blockages together with its directionality bring new technical challenges in the vehicular ... [more] | SIS2020-19 pp.48-53 |
| RCS | 2020-06-26 11:15 |
Online | Online | A Study on Gaussian Belief Propagation for Sparse Superposition Code in Massive NOMA Detection Ryuichi Kume, Shinsuke Ibi (Doshisha Univ.), Takumi Takahashi (Osaka Univ.), Hisato Iwai (Doshisha Univ.) RCS2020-45 |
In this paper, we propose an iterative detection strategy of Gaussian belief propagation (GaBP) for non-orthogonal multi... [more] | RCS2020-45 pp.133-138 |
| SP, EA, SIP | 2020-03-02 15:10 |
Okinawa | Okinawa Industry Support Center (Cancelled but technical report was issued) |
A Pattern Recognition Method Using Secure Sparse Representations in L0 Norm Minimization Takayuki Nakachi, Yitu Wang (NTT), Hitoshi Kiya (Tokyo Metro. Univ.) EA2019-130 SIP2019-132 SP2019-79 |
In this paper, we propose a privacy-preserving pattern recognition method using encrypted sparse representations in L0 n... [more] | EA2019-130 SIP2019-132 SP2019-79 pp.169-174 |
| CS, CAS | 2020-02-27 14:30 |
Kumamoto | An Estimation of Network Traffic Validation based on Sparse Coding Takayuki Nakachi, Yitu Wang (NTT) CAS2019-107 CS2019-107 |
With accurate network traffic prediction, future communication networks can realize self-management and enjoy intelligen... [more] | CAS2019-107 CS2019-107 pp.55-60 |
|
| 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 |
| IE, CS, IPSJ-AVM, ITE-BCT [detail] | 2019-12-05 11:40 |
Iwate | Aiina Center | [Special Talk]
Representation of moving-image's sparsity and its applications to adaptive moving-image restoration Takahiro Saito (Kanagawa Univ.) CS2019-75 IE2019-55 |
This talk states that statistical sparsity of a moving-image sequence can be properly represented in the domain of the 3... [more] | CS2019-75 IE2019-55 pp.29-34 |
| ITE-BCT, SIS | 2019-10-25 11:10 |
Fukui | Fukui International Activities Plaza | Image Compression in Encryption-then-Compression System Using Secure Sparse Representations Takayuki Nakachi (NTT), Hitoshi Kiya (Tokyo Metro. Univ.) SIS2019-21 |
n this paper, we propose a image compression method using secure sparse representations in Encryption-then-Compression (... [more] | SIS2019-21 pp.77-82 |
| OCS, LQE, OPE | 2019-10-18 10:20 |
Kagoshima | Intelligent Monitoring of Optical Fiber Transmission Using Sparse Coding Takayuki Nakachi, Yitu Wang, Tetsuro Inui, Takafumi Tanaka, Takahiro Yamaguchi, Katsuhiro Shimano (NTT) OCS2019-42 OPE2019-80 LQE2019-58 |
This paper proposes a sparse coding-based intelligent constellation diagram analyzer for optical fiber communications. I... [more] | OCS2019-42 OPE2019-80 LQE2019-58 pp.77-82 |
|
| 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 |
| IE, EMM, LOIS, IEE-CMN, ITE-ME, IPSJ-AVM [detail] | 2019-09-19 15:10 |
Niigata | Tokimeito, Niigata University | Secure sparse representations in L0 norm minimization Takayuki Nakachi (NTT), Hitoshi Kiya (Tokyo Metro. Univ.) LOIS2019-11 IE2019-24 EMM2019-68 |
In this paper, we propose a method to estimate secure sparse representations in L0 norm minimization, and evaluate the e... [more] | LOIS2019-11 IE2019-24 EMM2019-68 pp.25-30 |
| IT | 2019-09-06 10:35 |
Oita | Yufuin Kenshujo, Nippon Bunri University | The Recovery of (0,1)-Vector Based on Deep Neural Network Lantian Wei, Shan Lu, Hiroshi Kamabe (Gifu Univ.) IT2019-28 |
In this paper, we consider the recovery of sparse (0,1)-vectors from sparse signature matrix based on deep neural networ... [more] | IT2019-28 pp.13-17 |
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