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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| SeMI | 2024-01-18 13:30 |
Yamanashi | Raki House Kaiji | Enhancing Human Skeleton Estimation with Multi-Frame mmWave Radar Point Cloud-based Method Xintong Shi, Tomoaki Ohtsuki (Keio Univ.)  SeMI2023-52 |
Millimeter-Wave (mmWave) radar-based skeleton estimation has emerged as a focal point in the realm of human motion analy... [more] | SeMI2023-52 pp.18-21 |
| SRW, MICT, WBS | 2023-07-21 10:50 |
Niigata | Niigata Univ. TOKIMATE (Primary: On-site, Secondary: Online) |
A Study on RSSI Prediction using LSTM Considering Inter-Channel Correlation in SmartBAN Taito Toda, Takahiro Ito, Masaaki Yamanaka, Hirokazu Tanaka (Hiroshima City Univ.) WBS2023-21 SRW2023-19 MICT2023-18 |
The demand for healthcare monitoring in daily life using wearable devices is increasing as a result of the shortage of d... [more] | WBS2023-21 SRW2023-19 MICT2023-18 pp.37-42 |
| WIT | 2023-06-17 15:20 |
Okinawa | Okinawa Industry Support Center (Primary: On-site, Secondary: Online) |
Improved Visual Intentions Estimation Model Using Depth Information and Object Detection Sho Higa, Masakiyo Okuhama, Koji Yamada (Ryukyu Univ.), Shihoko Kamisato (NIT,Okinawa College) WIT2023-17 |
In this study, we propose an improved visual intention estimation model based on object detection to distinguish eye and... [more] | WIT2023-17 pp.76-77 |
| CNR, BioX | 2023-03-02 11:30 |
Oita | (Primary: On-site, Secondary: Online) |
A Study on Single Modal Ear Acoustic Personal Authentication System Sora Takagi (Kansai Univ.), Shunsuke Kita (ORIST), Yoshinobu Kajikawa (Kansai Univ.) BioX2022-73 CNR2022-39 |
Biometric authentication requires the provision of the user's personal biometric information.Currently, the mainstream b... [more] | BioX2022-73 CNR2022-39 pp.65-68 |
| MBE | 2022-07-23 13:50 |
Online | Online | Pilot Study on Early Prediction of Sleep Apnea Based on Heart Rate Variability Time-Series Forecasting Muhammad Shaufil Adha, Tomohiko Igasaki (Kumamoto Univ.) MBE2022-14 |
A widely accepted alternative to address the continuous positive airway pressure adherence problem is the use of its aut... [more] | MBE2022-14 pp.9-12 |
| IT | 2022-07-22 10:50 |
Okayama | Okayama University of Science (Primary: On-site, Secondary: Online) |
A study on deep learning-based cyber attack detection Ruei-Fong Hong, Qiangfu Zhao (UoA), Shih-Cheng Horng (CYUT) IT2022-22 |
Cyberattack is a broad term for cybercrime that includes any deliberate attack on a computer device, network or infrastr... [more] | IT2022-22 pp.36-41 |
| SANE | 2022-07-01 13:25 |
Ibaraki | (Primary: On-site, Secondary: Online) |
Prediction of Reentry Trajectories of Space Debris Using Long Short-Term Memory Akihiro Manaka, Makoto Tanaka (Tokai Univ.) SANE2022-15 |
In this study, debris reentry trajectory prediction was performed using NORAD No. 47782. LSTM was used for the predictio... [more] | SANE2022-15 pp.3-7 |
| SS | 2022-03-08 14:00 |
Online | Online | Multiple Feature Analysis for Problem Recommendation in Online Judge System Noah Sembu, Erina Makihara, Ryota Shinhama, Keiko Ono (Doshisha Univ.) SS2021-64 |
The Online Judge System (OJS) contains a wide variety of problems, and it is difficult for users to select an optimum pr... [more] | SS2021-64 pp.133-138 |
| NLP, MICT, MBE, NC (Joint) [detail] |
2022-01-22 14:55 |
Online | Online | Interference Prediction for SmartBAN Channel Migration Using LSTM Takahiro Ito, Aoi Nakamae (Hiroshima City Univ.), Masaaki Yamanaka (Japan Coast Guard Academy), Hirokazu Tanaka (Hiroshima City Univ.) NLP2021-110 MICT2021-85 MBE2021-71 |
Healthcare monitoring using wearable sensors is attracting attention. SmartBAN, which is a communication standard for me... [more] | NLP2021-110 MICT2021-85 MBE2021-71 pp.175-180 |
| R | 2021-06-12 14:25 |
Online | Online (Zoom) | A Study on Dual-task VAE with Weibull distribution for RUL estimation and application to Aero-Propulsion System data Ryosuke Sato, Mitsuhiro Kimura (Hosei Univ.) R2021-12 |
Remaining Useful Life (RUL) is one of the most important assessment measures in reliability engineering. Although sever... [more] |
R2021-12 pp.7-12 |
| EE, IEE-HCA | 2021-05-27 09:25 |
Online | Online | LSTM-based Neural Network Model for Predicting Solar Power Generation Kundjanasith Thonglek, Kohei Ichikawa (NAIST), Kazufumi Yuasa, Tadatoshi Babasaki (NTT-F) EE2021-2 |
Currently, the most popular renewable energy is solar power which reduces pollution consequences from using conventional... [more] | EE2021-2 pp.7-12 |
| SeMI, IPSJ-MBL, IPSJ-UBI [detail] | 2021-03-01 10:25 |
Online | Online | Fall Detection Based on LSTM Using Accelerometer Yoshiya Uotani, Chen Ye, Kohei Yamamoto, Tomoaki Ohtsuki (Keio) SeMI2020-59 |
In recent years, the increase in fall accidents among the elderly has become a problem with the aging of the population.... [more] | SeMI2020-59 pp.7-12 |
| MBE, NC (Joint) |
2020-12-18 15:40 |
Online | Online | Time-delayed LSTM for historical time series Prediction Rin Adachi, Jun Rokui (Univ of Shizuoka) NC2020-30 |
The research which applies machine learning to the social time series prediction is actively carried out. Among them, ma... [more] | NC2020-30 pp.13-18 |
| ITS, WBS, RCC | 2020-12-15 13:50 |
Online | Online | Classification of pedestrians existing in visible or blind areas using Doppler radar
-- An Approach Using Long Short-Term Memory -- Sora Hayashi, Daiki Isobe (Ritsumeikan Univ.), Kenshi saho (Toyama Pref. Univ.), Masao Masugi (Ritsumeikan Univ.) WBS2020-29 ITS2020-25 RCC2020-32 |
In this report, the walking positions of pedestrians, whether they are directly visible from the observation point or in... [more] | WBS2020-29 ITS2020-25 RCC2020-32 pp.121-125 |
| IE, IMQ, MVE, CQ (Joint) [detail] |
2020-03-05 11:35 |
Fukuoka | Kyushu Institute of Technology (Cancelled but technical report was issued) |
Pedestrian trajectory prediction considering consistent movement of surrounding people Kei Horiuchi, Yoshihiro Maeda (Tokyo Univ. of Science), Daisuke Sugimura (Tsuda Univ.), Takayuki Hamamoto (Tokyo Univ. of Science) IMQ2019-18 IE2019-100 MVE2019-39 |
In this paper, we propose a pedestrian trajectory prediction method considering the consistent movement of surrounding p... [more] | IMQ2019-18 IE2019-100 MVE2019-39 pp.23-26 |
| HCS | 2020-01-26 11:40 |
Oita | Room407, J:COM HorutoHall OITA (Oita) | Modeling for Infant Vocabulary Acquisition System using Deep Reinforcement Learning Masaki Taguchi, Yasuhiro Minami (UEC) HCS2019-73 |
We propose an infant vocabulary acquisition model that identifies psychological infant vocabulary development findings (... [more] | HCS2019-73 pp.111-116 |
| AI, IPSJ-ICS, JSAI-KBS, JSAI-DOCMAS, JSAI-SAI | 2019-03-09 17:00 |
Hokkaido | Please fill in Kouki Yoneda, Souichiro Yokoyama, Tomohisa Yamashita, Hidenori Kawamura (Hokudai) AI2018-57 |
(To be available after the conference date) [more] | AI2018-57 pp.25-30 |
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| EA, ASJ-H, ASJ-AA | 2018-07-25 15:20 |
Hokkaido | Hokkaido Univ. | Digital Modeling of Distortion Effect Using LSTM Machine-Learning Yuto Matsunaga, Naofumi Aoki, Yoshinori Dobashi, Tsuyoshi Yamamoto (Hokkaido Univ.) EA2018-26 |
This paper describes an experimental approach of modeling stomp boxes based on a machine learning approach. Our propose... [more] |
EA2018-26 pp.153-157 |
| CQ | 2018-07-20 13:50 |
Miyagi | Tohoku Univ. | Traffic Matrix Prediction based on Bidirectional Recurrent Neural Network and Long Short-Term Memory Van An Le, Phi Le Nguyen (Sokendai(The Graduate University for Advanced Studies)), Yusheng Ji (NII) CQ2018-40 |
Accurate prediction of the future network traffic plays an important role in various network problems (e.g. traffic engi... [more] | CQ2018-40 pp.51-56 |
| SIP, EA, SP, MI (Joint) [detail] |
2018-03-20 09:00 |
Okinawa | [Poster Presentation]
Anomaly Detection by Reconstructing Features from Subsampled Audio Signals Yohei Kawaguchi (Hitachi) EA2017-161 SIP2017-170 SP2017-144 |
We aim to reduce the cost of sound monitoring for maintain machinery by reducing the sampling rate, i.e., sub-Nyquist sa... [more] | EA2017-161 SIP2017-170 SP2017-144 pp.323-327 |
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