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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 145  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
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)
PN 2019-03-15
15:00
Okinawa Miyako Island Hirara Port Terminal Bldg. Fault-Tolerant Multipath Provisioning Scheme to Minimize Required Spectrum Resource in Elastic Optical Networks
Kenta Takeda, Takehiro Sato, Ryoichi Shinkuma, Eiji Oki (Kyoto Univ.) PN2018-96
This paper proposes a multipath provisioning scheme for fault tolerance to minimize required spectrum resource in EON. [more] PN2018-96
pp.77-83
ASN, MoNA, IPSJ-MBL, IPSJ-UBI [detail] 2019-03-05
09:40
Tokyo The University of Tokyo, Komaba Campus Reward-based Allocation for Mobile Crowdsensing in Real-time Prediction of Spatial Information
Rieko Takagi, Yuichi Inagaki, Ryoichi Shinkuma (Kyoto Univ.), Fatos Xhafa (UPC), Takehiro Sato, Eji Oki (Kyoto Univ.) MoNA2018-72
Real-time prediction of spatial information has attracted a lot of attention as a potential solution to social problems ... [more] MoNA2018-72
pp.53-58
MoNA 2019-01-16
15:20
Kyoto T. B. D. [Invited Lecture] A survey of research using machine learning presented at Globecom2018
Yoshinobu Yamada, Ryoichi Shinkuma (Kyoto Univ.) MoNA2018-65
(To be available after the conference date) [more] MoNA2018-65
pp.45-50
 Results 1 - 20 of 145  /  [Next]  
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