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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| NLP | 2023-05-13 10:50 |
Fukushima | Kenshin Koriyama Cultural Center (Koriyama, Fukushima) (Fukushima) | Study on the Effectiveness of Adaptive Gradient Algorithm with Momentum on Spatiotemporal Second-Order Dynamics Model Shahrzad Mahboubi, Hiroshi Ninomiya (SIT)  NLP2023-3 |
[more] | NLP2023-3 pp.11-15 |
| CCS | 2023-03-26 13:55 |
Hokkaido | RUSUTSU RESORT (Hokkaido) | Study on tge Implementation of AI for Generating Humorous Response Sentence to Image Using AutoEncoder and Pix2Seq Ryo Yamatomi, Shahrzad Mahboubi, Hiroshi Ninomiya (SIT) CCS2022-73 |
[more] | CCS2022-73 pp.59-62 |
| CCS, NLP | 2022-06-09 16:50 |
Osaka | (Osaka, Online) (Primary: On-site, Secondary: Online) |
A Study on Accelerating Stochastic Weight Difference Propagation with Momentum Term Shahrzad Mahboubi, Hiroshi Ninomiya (Shonan Inst. of Tech.) NLP2022-9 CCS2022-9 |
With the rapid development of the IoT, there has been an increasing need to process the data on microcomputers equipped ... [more] | NLP2022-9 CCS2022-9 pp.40-45 |
| NLP, MICT, MBE, NC (Joint) [detail] |
2022-01-21 15:35 |
Online | Online (Online) | On the Study of Stochastic Gradient Descent Learning using Weight Difference Propagation Shahrzad Mahboubi, Ryo Yamatomi, Hiroshi Ninomiya (Shonan Inst. of Tech.) NLP2021-88 MICT2021-63 MBE2021-49 |
[more] | NLP2021-88 MICT2021-63 MBE2021-49 pp.61-66 |
| NLP, MICT, MBE, NC (Joint) [detail] |
2022-01-21 16:00 |
Online | Online (Online) | On the Study of Second-Order Training Algorithm using Matrix Diagonalization based on Hutchinson estimation Ryo Yamatomi, Shahrzad Mahboubi, Hiroshi Ninomiya (Shonan Inst. Tec.) NLP2021-89 MICT2021-64 MBE2021-50 |
In this study, we propose a new training algorithm based on the second-order approximated gradient method, which aims to... [more] | NLP2021-89 MICT2021-64 MBE2021-50 pp.67-70 |
| NLP, NC (Joint) |
2020-01-24 13:10 |
Okinawa | Miyakojima Marine Terminal (Okinawa) | Optimization of CMOS operational amplifier using MOGA Hitoshi Kubo (Shizuoka Univ.), Hiroshi Ninomiya (Shonan Inst. of Tech.), Hideki Asai (Shizuoka Univ.) NLP2019-93 |
Multi-Objective Genetic Algorithm (MOGA) is an extended version of Genetic Algorithm (GA) for problems with multiple obj... [more] | NLP2019-93 pp.45-48 |
| NLP, MSS (Joint) |
2019-03-15 14:55 |
Fukui | Bunkyo Camp., Univ. of Fukui (Fukui) | On the Influence of Momentum term in quasi-Newton method Shahrzad Mahboubi (SIT), Indrapriyadarsini s (Shizuoka Univ.), Hiroshi Ninomiya (SIT), Hideki Asai (Shizuoka Univ.) NLP2018-137 |
The Nesterov's Accelerated quasi-Newton (NAQ) method was derived from the quadratic approximation of the error function ... [more] | NLP2018-137 pp.69-74 |
| NLP | 2017-07-13 13:25 |
Okinawa | Miyako Island Marine Terminal (Okinawa) | On the Efficiency of Limited-Memory quasi-Newton Training using Second-Order Approximation Gradient Model with Inertial Term Shahrzad Mahboubi, Hiroshi Ninomiya (SIT) NLP2017-32 |
In recent years, along with large-scale data, it is expected that the scale of neural network will be large too. Therefo... [more] | NLP2017-32 pp.23-28 |
| PRMU, SP, WIT, ASJ-H | 2016-06-13 11:15 |
Tokyo | (Tokyo) | Preliminary study on deep manifold embedding for 3D object pose estimation Hiroshi Ninomiya, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase (Nagoya Univ.), Norimasa Kobori, Kunimatsu Hashimoto (Toyota) PRMU2016-39 SP2016-5 WIT2016-5 |
Recently, 3D object pose estimation is being focused. The parametric eigenspace method is known as one of the fundamenta... [more] | PRMU2016-39 SP2016-5 WIT2016-5 pp.25-30 |
| NC, NLP (Joint) |
2016-01-29 12:10 |
Fukuoka | Kyushu Institute of Technology (Fukuoka) | Accelerated quasi-Newton Training using Nesterov's Gradient Method Hiroshi Ninomiya (SIT) NLP2015-141 |
This paper describes a new quasi-Newton based accelerated technique for training of neural networks. Recently, Nesterov’... [more] | NLP2015-141 pp.87-92 |
| VLD, CPSY, RECONF, IPSJ-SLDM, IPSJ-ARC [detail] | 2016-01-19 10:40 |
Kanagawa | Hiyoshi Campus, Keio University (Kanagawa) | Circuit Design of Reconfigurable Logic and Comparison of the Methods Junki Kato, Shigeyoshi Watanabe, Hiroshi Ninomiya, Manabu Kobayashi, Yasuyuki Miura (SIT) VLD2015-77 CPSY2015-109 RECONF2015-59 |
[more] | VLD2015-77 CPSY2015-109 RECONF2015-59 pp.1-6 |
| SP | 2015-10-16 11:15 |
Hyogo | Kobe Univ. (Hyogo) | Multi-modal speech recognition using deep bottleneck features Satoshi Tamura (Gifu Univ), Hiroshi Ninomiya (Nagoya Univ), Norihide Kitaoka (Tokushima Univ), Shin Osuga (Aisin Seiki), Yurie Iribe (Aichi Prefectural Univ), Kazuya Takeda (Nagoya Univ), Satoru Hayamizu (Gifu Univ) SP2015-69 |
In this paper, we propose a novel multi-modal speech recognition method which uses speech and lip images, employing Deep... [more] | SP2015-69 pp.57-62 |
| SDM, ICD | 2015-08-25 10:20 |
Kumamoto | Kumamoto City (Kumamoto) | Circuit Design of Reconfigurable Dynamic Logic and Estimation of Number of Elements Junki Kato, Shigeyoshi Watanabe, Hiroshi Ninomiya, Manabu Kobayashi, Yasuyuki Miura (SIT) SDM2015-66 ICD2015-35 |
[more] | SDM2015-66 ICD2015-35 pp.47-52 |
| ET | 2015-03-14 15:40 |
Tokushima | Shikoku Univ. Plaza (Tokushima) | Establishment of an Active Engineering Learning Center on the basis of a Visualization Hideaki Okazaki, Fumihiro Inoue (Shonan Inst. Tech.), Michiya Inoue (Tokyo D Univ), Fumio Ozaki, Toshiaki Kagawa, Hiroyuki Sato, Hiroshi Takahashi, Toshihiro Tachibana, Kaya Nagasawa, Hiroshi Ninomiya, Takako Nonaka, Hikaru Mizutani (Shonan Inst. Tech.) ET2014-93 |
We show an establishment of an active engineering learning center on the basis of a visualization, and especially presen... [more] | ET2014-93 pp.45-49 |
| RECONF, CPSY, VLD, IPSJ-SLDM [detail] | 2015-01-29 10:45 |
Kanagawa | Hiyoshi Campus, Keio University (Kanagawa) | Circuit Design and Valuation of Reconfigurable Logic Circuit. Junki Kato, Shigeyoshi Watanabe, Hiroshi Ninomiya, Manabu Kobayashi, Yasuyuki Miura (SIT) VLD2014-119 CPSY2014-128 RECONF2014-52 |
[more] | VLD2014-119 CPSY2014-128 RECONF2014-52 pp.35-40 |
| VLD, DC, IPSJ-SLDM, CPSY, RECONF, ICD, CPM (Joint) [detail] |
2014-11-27 16:50 |
Oita | B-ConPlaza (Oita) | Circuit Design of Reconfigurable Dynamic Logic Junki Kato, Shigeyoshi Watanabe, Hiroshi Ninomiya, Manabu Kobayashi, Yasuyuki Miura (Shonan Inst. of Tech.) CPM2014-126 ICD2014-69 |
[more] | CPM2014-126 ICD2014-69 pp.21-26 |
| ICD, SDM | 2014-08-05 14:20 |
Hokkaido | Hokkaido Univ., Multimedia Education Bldg. (Hokkaido) | Circuit Design of Reconfigurable Dynamic Logic Based on Double Gate MOSFETs Junki Kato, Shigeyoshi Watanabe, Hiroshi Ninomiya, Manabu Kobayashi, Yasuyuki Miura (SIT) SDM2014-78 ICD2014-47 |
[more] | SDM2014-78 ICD2014-47 pp.87-92 |
| NLP | 2013-07-09 10:00 |
Okinawa | Miyako Island Marine Terminal (Okinawa) | Dynamic Sample Size Selection based quasi-Newton Training for Multilayer Neural Networks Hiroshi Ninomiya (SIT) NLP2013-38 |
This paper describes a novel robust training algorithm based on quasi-Newton iteration with the dynamic sample size sele... [more] | NLP2013-38 pp.63-68 |
| NC, NLP | 2013-01-24 12:50 |
Hokkaido | Hokkaido University Centennial Memory Hall (Hokkaido) | Study of qusai-Newton training algorithm on parallel distributed environment Makoto Saiki, Yoshihiko Sakashita, Hiroshi Ninomiya (Shonan Inst. of Tech.) NLP2012-111 NC2012-101 |
This paper describes the feasibility of quasi-Newton method for training feedforward neural networks on the parallel dis... [more] | NLP2012-111 NC2012-101 pp.43-48 |
| IT | 2012-09-28 11:30 |
Gunma | Kusatsu Seminar House (Gunma) | A Quantizer Design Method Based on Mutual Information Criteria for MIMO System Manabu Kobayashi (SIT), Hideki Yagi (UEC), Hiroshi Ninomiya (SIT), Shigeichi Hirasawa (Waseda Univ.) IT2012-41 |
B. M. Kurkoski et al. have proposed a quantizer design method based on the maximization of the mutual information. Furt... [more] |
IT2012-41 pp.59-64 |
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