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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| SeMI, IPSJ-UBI, IPSJ-MBL | 2024-02-29 11:50 |
Fukuoka | Sensing and computing framework for sharing real-space experience Wataru Sano, Oishi Taisei, Ryusei Sugano, Ryoichi Shinkuma, Gabriele Trovato (SIT)  SeMI2023-74 |
Opportunities for digital-space experience increase through the metaverse. Increasing opportunities in digital-space exp... [more] | SeMI2023-74 pp.19-24 |
|
| CS, CQ (Joint) |
2023-05-19 11:35 |
Kagawa | Rexxam Hall (Kagawa Kenmin Hall) (Primary: On-site, Secondary: Online) |
[Invited Lecture]
An Experiment Environment Using Self-Standing Smart Poles for City Airspace Taku Yamazaki, Sumiko Miyata, Ryoichi Shinkuma, Takumi Miyoshi (Shibaura Inst. Tech.) CS2023-12 |
(To be available after the conference date) [more] | CS2023-12 p.32 |
| SeMI, IPSJ-UBI, IPSJ-MBL | 2023-03-01 10:40 |
Aichi | (Primary: On-site, Secondary: Online) |
Classification of human posture from 3D point-cloud data in office environment Junpei Watanabe, Ryoichi Shinkuma, Gabriele Trovato (SIT) SeMI2022-110 |
This report presents an edge computing system that can classify people’s postures in an office using a Light Detection ... [more] |
SeMI2022-110 pp.19-24 |
| ICTSSL | 2022-05-27 16:35 |
Toyama | University of Toyama (Primary: On-site, Secondary: Online) |
[Invited Talk]
3D sensor network for smart monitoring toward smart cities Ryoichi Shinkuma (SIT) ICTSSL2022-9 |
[more] | ICTSSL2022-9 pp.45-49 |
| IN, RCS, NV (Joint) |
2022-05-27 09:30 |
Kanagawa | Keio University (Hiyoshi Campus) (Primary: On-site, Secondary: Online) |
[Invited Talk]
Communication network control based on feature of data extracted by machine learning and its application example Ryoichi Shinkuma (SIT) IN2022-6 RCS2022-19 |
[more] | IN2022-6 RCS2022-19 pp.26-31(IN), pp.28-33(RCS) |
| SeMI, IPSJ-DPS, IPSJ-MBL, IPSJ-ITS | 2022-05-26 14:39 |
Okinawa | (Primary: On-site, Secondary: Online) |
Relational model for video-content grouping based on brain-activity information Taisei Oishi, Ryusei Sugano, Ryoichi Shinkuma (SIT), Naoya Maeda (NTT DATA), Satoshi Nishida (NICT) SeMI2022-7 |
Prior research had focused on estimating people's preferences by focusing on brain responses during video viewing among ... [more] | SeMI2022-7 pp.32-35 |
| SeMI, IPSJ-DPS, IPSJ-MBL, IPSJ-ITS | 2022-05-27 14:03 |
Okinawa | (Primary: On-site, Secondary: Online) |
Estimation of appropriate work spots by machine learning based on relationships in an office environment. Maho Abe, Ryusei Sugano, Yo Nakamura, Ryoichi Shinkuma (SIT) SeMI2022-16 |
(To be available after the conference date) [more] | SeMI2022-16 pp.75-78 |
| SeMI, IPSJ-DPS, IPSJ-MBL, IPSJ-ITS | 2022-05-27 14:21 |
Okinawa | (Primary: On-site, Secondary: Online) |
Edge system for providing blind zone information to moving vehicles in real time using LIDAR network Jumpei Negishi, Azuma Kenta, Ryoichi Shinkuma (SIT) SeMI2022-17 |
This report proposes an edge system that extracts mobility blind spot information from streaming data transmitted from L... [more] | SeMI2022-17 pp.79-82 |
| SeMI, IPSJ-DPS, IPSJ-MBL, IPSJ-ITS | 2022-05-27 14:39 |
Okinawa | (Primary: On-site, Secondary: Online) |
Automation of spatial calibration for point cloud data acquired by multiple heterogeneous LIDARs Katsuki Teraoka, Kenta Azuma, Ryoichi Shinkuma (SIT) SeMI2022-18 |
This report proposes a system that enables automation of spatial calibration in a 3D sensor network consisting of multip... [more] | SeMI2022-18 pp.83-86 |
| SRW, SeMI, CNR (Joint) |
2020-11-27 09:20 |
Online | Online | Bandwidth allocation for multiple LIDAR sensors based on spatial importance of point-cloud data Ryo Otsu, Ryoichi Shinkuma, Takehiro sato, Eiji Oki (KU) SeMI2020-36 |
This paper addresses the bandwidth allocation to multiple Light Detection and Ranging (LIDAR) sensors in smart monitorin... [more] | SeMI2020-36 pp.82-87 |
| SRW, SeMI, CNR (Joint) |
2020-11-27 09:40 |
Online | Online | Estimation of spatial importance of 3D sensor data for real-time smart monitoring using machine learning Masamichi Oka, Ryoichi Shinkuma, Eiji Oki, Takehiro Sato (Kyoto Univ.), Takanori Iwai, Koichi Nihei, Takahashi Eiji, Dai Kanetomo, Kozo Satoda (NEC) SeMI2020-37 |
[more] | SeMI2020-37 pp.88-93 |
| MWP, PN, EMT, PEM, IEE-EMT [detail] | 2020-01-31 11:45 |
Kyoto | Dosisha Univ. | Performance of routing and spectrum slot allocation model for multipath provisioning in elastic optical networks Kenta Takeda, Takehiro Sato, Ryoichi Shinkuma, Eiji Oki (Kyoto Univ.) PN2019-50 EMT2019-90 MWP2019-64 |
Multipath provisioning (MPP) uses multiple disjoint paths for data transmission to tolerate network failures. This paper... [more] | PN2019-50 EMT2019-90 MWP2019-64 pp.97-102 |
| NS, RCS (Joint) |
2019-12-20 13:30 |
Tokushima | Tokushima Univ. | [Encouragement Talk]
Service chain provisioning model with relaxation of virtual network function visit order and non-loop constraints Naoki Hyodo, Takehiro Sato, Ryoichi Shinkuma, Eiji Oki (Kyoto Univ.) NS2019-158 |
This paper presents a Virtual Network Function (VNF) placement model for Service Chaining (SC) which minimizes the cost ... [more] | NS2019-158 pp.127-132 |
| RISING (2nd) |
2019-11-26 10:30 |
Tokyo | Fukutake Learning Theater, Hongo Campus, Univ. Tokyo | [Poster Presentation]
Prioritized Transmission of Mobile IoT Data Using Machine Learning Models Yuichi Inagaki, Ryoichi Shinkuma, Takehiro Sato, Oki Eiji (Kyoto Univ.) |
Predicting real-time spatial information from data collected by the mobile Internet of Things (IoT) devices is one solut... [more] | |
| RISING (2nd) |
2019-11-27 13:55 |
Tokyo | Fukutake Learning Theater, Hongo Campus, Univ. Tokyo | [Poster Presentation]
Modeling of Utility Function for Real-time Prediction of Spatial Information Using Machine Learning Keiichiro Sato, Ryoichi Shinkuma, Takehiro Sato, Eiji Oki (Kyoto Univ.), Takahiro Iwai, Takeo Onishi, Takahiro Nobukiyo, Dai Kanetomo, Kozo satoda (System platform Research Labs, NEC Corporation) |
Real-time prediction of spatial information has attracted a lot of attention. Machine learning enables us to provide rea... [more] | |
| SRW, SeMI, CNR (Joint) |
2019-11-05 15:20 |
Tokyo | Kozo Keisaku Engineering Inc. | [Invited Talk]
Mobile IoT: Past and Future Ryoichi Shinkuma (Kyoto Univ.) SRW2019-26 SeMI2019-73 CNR2019-20 |
[more] | SRW2019-26 SeMI2019-73 CNR2019-20 pp.21-26(SRW), pp.59-64(SeMI), pp.21-26(CNR) |
| NS, IN, CS, NV (Joint) |
2019-09-05 15:25 |
Miyagi | Research Institute of Electrical Communication, Tohoku Univ. | [Invited Talk]
Cooperation and data assessment in heterogeneous networks toward IoT era Ryoichi Shinkuma (Kyoto Univ.) NS2019-90 |
In conventional networks, since communication devices were homogeneous and a central entity operated the networks, they ... [more] | NS2019-90 pp.7-12 |
| RCS, SAT (Joint) |
2019-08-23 11:45 |
Aichi | Nagoya University | Wireless Network Control Enabled by Data Assessment Using Machine Learning Ryoichi Shinkuma, Takayuki Nishio (Kyoto Univ.) RCS2019-166 |
The real-time prediction of spatial information is promising for next-generation mobile networks. Recent developments in... [more] | RCS2019-166 pp.109-112 |
| SeMI, RCS, NS, SR, RCC (Joint) |
2019-07-10 13:50 |
Osaka | I-Site Nanba（Osaka） | [Encouragement Talk]
Utility-function modeling scheme for real-time prediction of spatial information Keiichiro Sato, Ryoichi Shinkuma, takehiro Sato, Eiji Oki (Kyoto Univ.), Takahiro Iwai, Takeo Onishi, Takahiro Nobukiyo, Dai Kanetomo, Kozo satoda (System platform Research Labs, NEC Corporation) SeMI2019-21 |
Real-time prediction of spatial information has attracted a lot of attention.However, due to the strict limitation of ba... [more] | SeMI2019-21 pp.19-22 |
| RCS, IN, NV (Joint) |
2019-05-17 13:20 |
Kanagawa | Keio University | [Invited Lecture]
Cooperation in heterogeneous networks and future vision Ryoichi Shinkuma (Kyoto Univ.) IN2019-11 RCS2019-34 |
[more] | IN2019-11 RCS2019-34 pp.43-47(IN), pp.65-69(RCS) |
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