Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
RCS, SR, SRW (Joint) |
2024-03-13 13:25 |
Tokyo |
The University of Tokyo (Hongo Campus), and online (Primary: On-site, Secondary: Online) |
Underwater Acoustic Communication Between Autonomous Surface Vehicle and Autonomous Underwater Vehicle in Shallow Sea Channel
-- Experimental Demonstration of the Mobile Communication Between High Speed Vehicles Using a Multi-channel Decision Feedback Equalizer Approach -- Yukihiro Kida, Mitsuyasu Deguchi, Takuya Shimura (JAMSTEC), Narihiro Iwama (ATLA) RCS2023-260 |
Underwater acoustic communication is known for one of the most severe doubly selective propagation environment with sign... [more] |
RCS2023-260 pp.36-41 |
SeMI, IPSJ-UBI, IPSJ-MBL |
2024-03-01 10:30 |
Fukuoka |
|
A Preliminary Study on Parameter Optimization Using a Backpropagation Algorithm for a Neonatal Thermal Model Natsumi Sakamoto, Hiroki Kudo, Akira Uchiyama (Osaka Univ.), Keisuke Hamada (Nagasaki Harbor Medical Center), Eiji Hirakawa (Kagoshima City Hospital) SeMI2023-81 |
Neonates need temperature management in incubators due to their underdeveloped thermoregulatory functions. Traditional m... [more] |
SeMI2023-81 pp.60-65 |
RISING (3rd) |
2023-10-31 10:45 |
Hokkaido |
Kaderu 2・7 (Sapporo) |
[Poster Presentation]
Study on Beamforming Feedback in Wireless LANs and Singular Value Decomposition Hiroki Shimomura (Kyoto Univ.), Koji Yamamoto (KIT), Takayuki Nishio (Tokyo Tech.), Akihito Taya (Tokyo Univ.) |
We investigated the properties of beamforming feedback (BFF) facilitated by singular value decomposition (SVD) as a step... [more] |
|
RISING (3rd) |
2023-10-31 14:00 |
Hokkaido |
Kaderu 2・7 (Sapporo) |
[Poster Presentation]
Optimal Compression Rate for Multiple Data Compression Techniques in Data Parallel Distributed Deep Learning Ryudai Fukuda, Takuji Tachibana (Univ. Fukui) |
In distributed deep learning, where multiple processors are used, the learning time can be significantly reduced by exec... [more] |
|
NS |
2023-10-05 10:10 |
Hokkaido |
Hokkaidou University + Online (Primary: On-site, Secondary: Online) |
[Encouragement Talk]
Communication Scheduling Based on Heuristic Algorithm in Distributed Deep Learning Ryudai Fukuda, Takuji Tachibana (Univ. Fukui) NS2023-86 |
In distributed deep learning, where multiple processors are used, the learning time can be significantly reduced by exec... [more] |
NS2023-86 pp.83-88 |
CS |
2023-07-28 14:50 |
Tokyo |
Hachijo-machi Chamber of Commerce and Industry |
Improving position estimation accuracy method by reducing RSSI fluctuations in BLE fingerprinting-based indoor positioning Jingshi Qian, Nobuyoshi Komuro (Chiba Univ.) CS2023-58 |
The complex indoor environment will reflect and absorb the RSSI (Received Signal Strength Indicator) from the sensor. Be... [more] |
CS2023-58 pp.163-168 |
NS, ICM, CQ, NV (Joint) |
2022-11-24 13:00 |
Fukuoka |
Humanities and Social Sciences Center, Fukuoka Univ. + Online (Primary: On-site, Secondary: Online) |
Optimal Data Communication Scheduling Considering Multiple Data Compression Techniques in Distributed Deep Learning Fukuda Ryudai, Takuji Tachibana (Univ. Fukui) NS2022-105 |
In distributed deep learning, which uses multiple processors, the training time can be greatly reduced by executing the ... [more] |
NS2022-105 pp.29-34 |
ITE-BCT, OCS, IEE-CMN, OFT |
2022-11-11 13:00 |
Miyagi |
Forest-Sendai (Primary: On-site, Secondary: Online) |
Learning-based digital back propagation considering cross-phase modulation in wavelength-division multiplexed transmission systems Takashi Inoue, Ryosuke Matsumoto, Shu Namiki (AIST) OCS2022-44 |
We propose a scheme to compensate waveform distortion of optical signals due to fiber nonlinearity in wavelength-divisio... [more] |
OCS2022-44 pp.24-29 |
SIS, IPSJ-AVM |
2022-06-10 11:20 |
Fukuoka |
KIT(Wakamatsu Campus) (Primary: On-site, Secondary: Online) |
Sugar content detection using wireless LAN system for sucrose aqueous solution Souta Yakura, Naoto Sasaoka, Tadao Nakagawa, Yoshihiro Takemura (Tottori Univ.) SIS2022-8 |
Currently, Japan’s agricultural industry is facing various problems such as farming population. To solve such problems ,... [more] |
SIS2022-8 pp.36-40 |
SeMI, IPSJ-MBL, IPSJ-UBI |
2022-03-07 14:25 |
Online |
Online |
Non-Backtracking Consensus Algorithm for Sensor Networks Akihito Taya (Aoyama Gakuin Univ.) SeMI2021-86 |
This paper proposes a non-backtracking consensus algorithm for sensor networks. By focusing on the amount of information... [more] |
SeMI2021-86 pp.19-24 |
SeMI |
2022-01-20 15:20 |
Nagano |
(Primary: On-site, Secondary: Online) |
[Short Paper]
A Study of Beamforming Feedback-based Model-driven Angle of Departure Estimation Sohei Itahara (Kyoto Univ.), Takayuki Nishio (Kyoto Univ./Tokyo Tech.), Koji Yamamoto (Kyoto Univ.) SeMI2021-68 |
This paper introduces the angle of departure (AoD) estimation method [1] using the multiple signal classification (MUSIC... [more] |
SeMI2021-68 pp.59-61 |
MBE, NC (Joint) |
2021-10-28 15:55 |
Online |
Online |
A Study on Improvement Learning Performance with Chaos Neurons Renshi Nagasawa, Masahiro Nakagawa (NUT) NC2021-23 |
In the backpropagation method in neural networks, the problem is that the energy converges to the local minimum. On the... [more] |
NC2021-23 pp.28-33 |
IN, CCS (Joint) |
2021-08-05 14:25 |
Online |
Online |
Digital Implement of 3-layered Neural Networks with Stochastic Activation, Shunting Inhibition, and a Dual-rail Backpropagation Yoshiaki Sasaki, Seiya Muramatsu, Kohei Nishida, Megumi Akai-Kasaya, Tetsuya Asai (Hokkaido Univ.) CCS2021-16 |
Stochastic computing (SC) is an arithmetic technique that enables various operations to be performed with a small number... [more] |
CCS2021-16 pp.7-13 |
NC, MBE (Joint) |
2021-03-05 13:25 |
Online |
Online |
Applying Ensemble Learning in Relay BP Keisuke Toyama, Yukari Yamauchi (Nihon Univ.) NC2020-70 |
Convolutional Neural Network (CNN) is one of the network models that can produce highly accurate output even though it u... [more] |
NC2020-70 pp.157-162 |
RCS, AP, UWT (Joint) |
2020-11-26 11:20 |
Online |
Online |
[Invited Lecture]
Adaptive digital down-conversion for underwater acoustic communication Mitsuyasu Deguchi, Yukihiro Kida, Takuya Shimura (JAMSTEC) AP2020-86 RCS2020-125 |
In underwater acoustic communication, effects of the Doppler shift is much larger than that of the radio communication i... [more] |
AP2020-86 RCS2020-125 pp.72-77(AP), pp.87-92(RCS) |
MBE, NC, NLP, CAS (Joint) [detail] |
2020-10-29 16:10 |
Online |
Online |
Numerical research on effects of quantization in SNN learned by backpropagation Yumi Watanabe, Jun Ohkubo (Saitama Univ.) NC2020-14 |
There are many studies to quantize the parameters of neural networks. For example, while there are methods of quantizing... [more] |
NC2020-14 pp.29-33 |
IBISML |
2020-10-22 14:25 |
Online |
Online |
Improvement of the robustness by increasing the size of feedback vertex set Masaki Chujyo, Yukio Hayashi (JAIST) IBISML2020-31 |
Many real world networks such as power grid and communication networks are commonly scale-free, but highly vulnerable ag... [more] |
IBISML2020-31 pp.55-60 |
AP, SANE, SAT (Joint) |
2020-07-17 10:45 |
Online |
Online |
Computation on Circularly Polarized Electromagnetic Wave Backscattering by A Tree Target using FDTD Method Xiangyu Huang, Mohammad Nasucha, Josaphat T. Sri sumantyo, Cahya E.Santosa (Chiba Univ) SANE2020-18 |
Chiba University is developing Circularly Polarized Synthetic Aperture Radar (CP-SAR). Understanding electromagnetic wav... [more] |
SANE2020-18 pp.11-15 |
RCS |
2020-04-23 - 2020-04-24 |
Online |
Online |
Generalization of Performance Analysis on OFDM Pilot-Aided Ambient Backscatter Communications Takanori Hara, Ryuhei Takahashi, Koji Ishibashi (The Univ. of Electro-Communications) RCS2020-9 |
As a promising scheme to transmit the information with ultra-low-power, ambient backscatter communication (AmBC) exploit... [more] |
RCS2020-9 pp.49-54 |
NC, MBE (Joint) |
2020-03-05 10:20 |
Tokyo |
University of Electro Communications (Cancelled but technical report was issued) |
An extension of the H_infinity learning to deep neural networks Yasuhiro Sugawara, Kiyoshi Nishiyama (Iwate University) NC2019-92 |
In recent years, deep neural networks have achieved remarkable research results. In this study, we propose a method to e... [more] |
NC2019-92 pp.95-100 |