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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 40  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
IE, ITS, ITE-MMS, ITE-ME, ITE-AIT [detail] 2023-02-21
11:10
Hokkaido Hokkaido Univ. [Special Talk] Study of Probability Modeling for Lossless Image Coding Using Example Search and Adaptive Prediction
Hiroki Kojima (KDDI), Yasuyo Kita, Ichiro Matsuda (Tokyo Univ. of Science) ITS2022-46 IE2022-63
Many efficient lossless image coding methods predict the next pel value to be coded from the pels already coded, and rem... [more] ITS2022-46 IE2022-63
p.25
RCC, ITS, WBS 2022-12-14
16:00
Shiga Ritsumeikan Univ. BKC
(Primary: On-site, Secondary: Online)
Effects of Data Transmission Loss Probability on Control Quality for Wireless Formation Flight of Drones
Kaito Tachi, Chedlia Ben Naila, Hiraku Okada, Masaaki Katayama (Nagoya Univ.) WBS2022-53 ITS2022-29 RCC2022-53
This paper focuses on a formation flight of drones flying in a straight line while maintaining an equal separation dista... [more] WBS2022-53 ITS2022-29 RCC2022-53
pp.103-107
CAS, NLP 2022-10-20
14:55
Niigata
(Primary: On-site, Secondary: Online)
Hierarchical Lossless Coding with Arithmetic Coders for Each CNN Predictor
Kazuki Nakashima, Ryo Nakazawa, Hideharu Toda, Hisashi Aomori (Chukyo Univ.), Tsuyoshi Otake (Tamagawa Univ.), Ichiro Matsuda, Susumu Itoh (TUS) CAS2022-23 NLP2022-43
We have been developing a scalable lossless coding method using the cellular neural networks (CNN) as predictors.
This ... [more]
CAS2022-23 NLP2022-43
pp.20-24
IT 2022-07-21
14:05
Okayama Okayama University of Science
(Primary: On-site, Secondary: Online)
New algorithms for computing the correct decoding probability exponent for lossy source coding
Yutaka Jitsumatsu (Tokyo Tech.), Yasutada Oohama (UEC) IT2022-17
In a 1976 paper, Arimoto proposed an algorithm for computing the error exponent and the correct decoding probability exp... [more] IT2022-17
pp.10-11
IN, RCS, NV
(Joint)
2022-05-26
15:45
Kanagawa Keio University (Hiyoshi Campus)
(Primary: On-site, Secondary: Online)
[Tutorial Lecture] Distributed Lossy Multi-terminal Communications over Fading MAC and Decision Making (This tutorial is funded by IoTAD-CEO project under CominLab)
Tad Matsumoto (IMT-Atlantique, Brest, France/Professor Emeritus, JAIST), Elsa Dupraz (IMT-Atlantique, Brest, France) RCS2022-18
Network Information Theory is an extension of Shannon’s Information Theory to Networks. We believe that the key to the s... [more] RCS2022-18
pp.26-27
R 2021-06-12
15:25
Online Online (Zoom) Performance evaluation of heterogenous cellular networks using stochastic Petri nets
Zhiyi Zhu, Junjun Zheng (Ritsumeikan Univ.), Eiji Takimoto (H.I.T.) R2021-14
In recent decades, the explosive growth of cellular network technology results in an ongoing increase in data transmissi... [more] R2021-14
pp.19-24
IE, SIP, BioX, ITE-IST, ITE-ME [detail] 2021-06-03
16:00
Online Online Fast Implementation of the Lossless Image Coding Method Based on Example Search and Probability Model Optimization
Hiroki Kojima, Yusuke Kameda, Yasuyo Kita, Ichiro Matsuda, Susumu Itoh (Tokyo Univ of Science.) SIP2021-3 BioX2021-3 IE2021-3
We previously proposed a lossless image coding method based on example search and probability model optimization. In the... [more] SIP2021-3 BioX2021-3 IE2021-3
pp.10-14
IE 2021-01-21
14:00
Online Online [Invited Talk] Lossless Image/Video Coding Method Based on Probability Model Estimation and Optimization
Kyohei Unno (KDDI Research) IE2020-36
In this talk, the lossless image/video coding method that is proposed by the author is introduced. The proposed method e... [more] IE2020-36
p.8
NC, MBE
(Joint)
2020-03-05
13:00
Tokyo University of Electro Communications
(Cancelled but technical report was issued)
Bayesian learning curve for the case when the optimal distribution is not unique
Shuya Nagayasu, Sumio Watanabe (Tokyo Tech) NC2019-94
Bayesian inference is a widely used statistical method. Asymptotic behaviors of generalization loss and free energy in B... [more] NC2019-94
pp.107-112
NS, ICM, CQ, NV
(Joint)
2019-11-22
10:15
Hyogo Rokkodai 2nd Campus, Kobe Univ. Transmission scheduling for tandemly-connected sensor networks with non-uniform packet generation rates
Ryosuke Yoshida, Ryota Kimura, Masahiro Shibata, Masato Tsuru (Kyutech) CQ2019-98
To remotely monitor a power transmission tower's network in a mountainous area where a communication infrastructure is u... [more] CQ2019-98
pp.53-58
IT, ISEC, WBS 2019-03-07
09:30
Tokyo University of Electro-Communications Analysis of Zero-Redundancy Estimator with a Finite Window for Markovian Source -- When the Statewise Alphabets are Unknown --
Yusuke Hashimoto, Tstutomu Kawabata (Univ. of Electro-Comm.) IT2018-89 ISEC2018-95 WBS2018-90
A Bayesian (Laplace or Krichevski-Trofimov) estimator for Markov source can be used to build a lossless
source code. Ho... [more]
IT2018-89 ISEC2018-95 WBS2018-90
pp.85-90
IN, NS
(Joint)
2019-03-05
10:00
Okinawa Okinawa Convention Center A proposed of call admission control maximizing the number of general calls from out of disaster area considering the priority of emergency and general calls in the disaster area
Kawsae Tatsuya, Sumiko Miyata (SIT) IN2018-115
When a disaster occurs, the demands for telephone calls increase because of safety confirmation and emergency request.Th... [more] IN2018-115
pp.187-192
IN, RCS, NV
(Joint)
2018-05-11
11:10
Kanagawa Keio University [Invited Talk] Lossy forwarding over non-orthogonal MAC channels
Tadashi Matsumoto, Shen Qian (JAIST), Jiguang He (UOulu) IN2018-7 RCS2018-34
 [more] IN2018-7 RCS2018-34
p.35(IN), p.71(RCS)
SSS 2018-04-24
16:15
Tokyo   A study of Fukushima nuclear power plant accidents by a viewpoint of PSA (Reconsideration)
Takeshi Matsuoka (Utsunomiya Univ.) SSS2018-6
On 11th March, 2011, most sever nuclear power plant accidents in the history have been occurred at the Fukushima site du... [more] SSS2018-6
pp.23-26
CCS 2018-03-26
10:00
Tokyo Tokyo Univ. of Sci. (Morito Memorial Hall) Suppression Method of Mode Collapse in Generative Adversarial Nets
Shinya Hidai, Hidehiro Nakano, Arata Miyauchi (Tokyo City Univ.) CCS2017-33
Generative Adversarial Nets (GAN) is constituted by two neural networks, Generator and Discrminator. Generator creates d... [more] CCS2017-33
pp.1-6
CQ
(2nd)
2018-01-20
12:50
Tokyo Nishiwaseda Campus, Waseda Univ. [Poster Presentation] A Study of a Packet Loss Estimation Using Importance Sampling in Networks with Unknown Traffic
Masahiro Terauchi, Kohei Watabe, Kenji Nakagawa (Nagaoka Univ. of Technology)
Techniques for measuring the packet loss probability with high accuracy are important to ensure Service Level Agreements... [more]
OCS 2015-07-30
11:25
Tokyo Tokyo Tech Front Experimental Demonstration and Evaluation of Signal Performance Improvement by Walsh-Hadamard Transform for Super-Channel beyond 100Gbps
Akira Masuda, Kohki Shibahara, Shingo Kawai, Mitsunori Fukutoku (NTT) OCS2015-29
Super-channel transmission is a promising technique to increase a channel capacity in next generation optical transport ... [more] OCS2015-29
pp.25-29
ICD, CPSY 2014-12-01
10:25
Tokyo Kikai-Shinko-Kaikan Bldg. Improvement of VoIP Service Quality by Packet Destruction based on Probabilistic Distribution
Hayato Sakurai, Eiji Kamioka (SIT) ICD2014-74 CPSY2014-86
With advancement of IP-based information and communication technologies, VoIP services have been used in various scenes.... [more] ICD2014-74 CPSY2014-86
pp.7-12
ICM, CQ, NS, NV
(Joint)
2014-11-13
16:00
Kochi Kochi-City-Culture-Plaza CUL-PORT [Invited Talk] Network Performance Evaluation by High Speed Simulation
Kenji Nakagawa (Nagaoka Univ. of Tech.) NS2014-135 CQ2014-78 ICM2014-26
In this paper, we present a high speed simulation method for estimating the packet loss probability of a queue. Usual M... [more] NS2014-135 CQ2014-78 ICM2014-26
pp.39-45(NS), pp.39-45(CQ), pp.57-63(ICM)
ICM, CQ, NS, NV
(Joint)
2014-11-14
09:50
Kochi Kochi-City-Culture-Plaza CUL-PORT Understanding the Impact of Scale-Free Structure on End-to-End TCP Performance Using Fluid-Based Analysis
Yusuke Sakumoto (Tokyo Metropolitan Univ.), Hiroyuki Ohsaki (Kwansei Gakuin Univ.) CQ2014-81
The scale-free structure is one of the most well-known properties of the Internet as a complex network. Many researcher... [more] CQ2014-81
pp.59-64
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