| IEICE Technical Committee Submission System Conference Schedule |
Online Proceedings [Sign in] Tech. Rep. Archives |
All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| EA, US (Joint) |
2023-12-22 15:20 |
Fukuoka | [Poster Presentation]
Large area growth of c-axis tilted Sc0.4Al0.6N thin films using planar sputtering with rectangular cathode Naoki Ishii, Yhoho Shimano, Takahiko Yanagitani (Waseda Univ.)  US2023-65 |
c-axis normal ScAlN thin films with Sc concentration exceeding 40% possess high thickness extensional mode electromechan... [more] | US2023-65 pp.53-58 |
|
| SIP | 2020-08-28 13:30 |
Online | Online | [Invited Talk]
Image smoothing based on L0 gradient regularization and its applications Ryo Matsuoka (Univ. of Kitakyushu) SIP2020-37 |
This talk outlines research on image processing based on L0 gradient regularization that promotes sparseness in the grad... [more] | SIP2020-37 p.33 |
| 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 |
| MBE, NC (Joint) |
2018-03-14 11:15 |
Tokyo | Kikai-Shinko-Kaikan Bldg. | Evaluation of feature selection accuracy using sparse classification algorithm based on L0-norm optimization Naoki Ishibashi, Noriki Ito, Masashi Sato (UEC Tokyo), Yoshiyuki Kabashima (Tokyo Tech), Yoichi Miyawaki (UEC Tokyo/JST PRESTO) NC2017-91 |
Classification often suffers from overfitting if applied to a dataset of small sample size and high dimensionality. Dime... [more] | NC2017-91 pp.139-144 |
| NC, IPSJ-BIO, IBISML, IPSJ-MPS [detail] | 2016-07-06 14:55 |
Okinawa | Okinawa Institute of Science and Technology | Classification analysis of high-dimensional data based on L0-norm optimization. Noriki Ito, Masashi Sato (UEC Tokyo), Yoshiyuki Kabashima (Tokyo Tech), Yoichi Miyawaki (UEC Tokyo) NC2016-14 |
Advances in sensing devices allow us to measure high-dimensional data easily, but the sample size is often limited becau... [more] | NC2016-14 pp.223-228 |
| ITS, IE, ITE-AIT, ITE-HI, ITE-ME, ITE-MMS, ITE-CE [detail] | 2016-02-22 16:15 |
Hokkaido | Hokkaido Univ. | Reduction of computational cost in ICA-DCT hybrid coding for still image Kazuya Kawamura, Masashi Kameda (Iwate Prefectural Univ.) ITS2015-72 IE2015-114 |
Independent Component Analysis (ICA) can derive the inherent set of bases which are correspond to local features of a gi... [more] | ITS2015-72 IE2015-114 pp.113-118 |
| IE, ITS, ITE-AIT, ITE-HI, ITE-ME, ITE-MMS, ITE-CE [detail] | 2015-02-23 15:15 |
Hokkaido | Hokkaido Univ. | Improvement of PNG Image Compression by Optimizing Filter Selection Teppei Takahashi, Akira Kubota (Chuo Univ.) ITS2014-59 IE2014-86 |
In this paper, we propose an optimal filter selection to improve PNG (Portable Network Graphics) compression. This metho... [more] | ITS2014-59 IE2014-86 pp.217-221 |
| IBISML | 2011-03-28 16:50 |
Osaka | Nakanoshima Center, Osaka Univ. | Enumerating Feature-Sets with Submodularity Yoshinobu Kawahara (Osaka Univ.), Koji Tsuda (AIST), Takashi Washio (Osaka Univ.), Akiko Takeda (Keio Univ.), Shin-ichi Minato (Hokkaido Univ.) IBISML2010-113 |
Selecting relevant features is a fundamental task in machine learning. Although many approaches have been investigated s... [more] | IBISML2010-113 pp.63-68 |
[Return to Top Page]