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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| CQ, MIKA (Joint) (2nd) |
2023-08-30 15:00 |
Fukushima | Tenjin-Misaki Sports Park | [Poster Presentation]
Estimation of the timing suitable for collect pear pollen using machine learning Keita Endo (NIT), Tomotaka Kimura (Doshisha Univ.), Hiroyuki Shimizu (NIT), Tomohito Shimada (SATRC), Akane Shibasaki (SAFPC), Ryota Fujinuma (DKK), Yoshihiro Takemura (Tottori Univ.), Takefumi Hiraguri (NIT) |
Pear pollination is generally done by artificial pollination, which requires the collection of pollen. Pollen collection... [more] | |
| LOIS, IPSJ-DC | 2023-08-04 14:20 |
Kyoto | Kyoto Tachibana University, Keisei-Kan, 1-G106 (Primary: On-site, Secondary: Online) |
Analysis of noting behaviors by students in video lectures (Sixth report) Eiji Watanabe (Konan Univ.), Takashi Ozeki (Fukuyama Univ.), Takeshi Kohama (Kindai Univ.)  LOIS2023-5 |
In this report, we analyze learning behaviors of students for video lectures assuming on demand type lectures. Here, we ... [more] | LOIS2023-5 pp.12-17 |
| SeMI, IPSJ-ITS, IPSJ-MBL, IPSJ-DPS | 2023-05-18 18:20 |
Okinawa | Okinawa Institute of Science and Technology (OIST) (Primary: On-site, Secondary: Online) |
Mobility-Aware Timing Control of Parameter Aggregation in Edge Federated Learning Shota Ono (Univ. of Tokyo), Taku Yamazaki, Takumi Miyoshi (Shibaura Inst. of Tech.), Akihito Taya, Yuuki Nishiyama, Kaoru Sezaki (Univ. of Tokyo) SeMI2023-7 |
Services that utilize region-specific data collected by onboard vehicle sensors have been attracting attention. In thes... [more] |
SeMI2023-7 pp.26-29 |
| PRMU, IBISML, IPSJ-CVIM [detail] | 2023-03-02 09:20 |
Hokkaido | Future University Hakodate (Primary: On-site, Secondary: Online) |
Relation Between Shape/Texture Biases and Double-Descent Phenomenon in Visual Recognition Shuya Takahashi (Tokyo Denki Univ./AIST), Nakamasa Inoue, Rio Yokota (Tokyo Tech), Hirokatsu Kataoka (AIST), Eisaku Maeda (Tokyo Denki Univ.) PRMU2022-60 IBISML2022-67 |
Under certain conditions, the learning performance of machine learning undergoes a strange phenomenon called double-desc... [more] | PRMU2022-60 IBISML2022-67 pp.13-16 |
| NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] | 2022-06-29 15:00 |
Okinawa | (Primary: On-site, Secondary: Online) |
Emergence of Dynamical Orthogonal Basis Acquiring Large Memory Capacity in Modular Reservoir Computing Yuji Kawai (Osaka Univ.), Jihoon Park (NICT/Osaka Univ.), Ichiro Tsuda (Chubu Univ.), Minoru Asada (IPUT/Osaka Univ./Chubu Univ./NICT) NC2022-28 IBISML2022-28 |
The brain's ability to generate complex spatiotemporal patterns with a specific timing is essential for motor learning a... [more] | NC2022-28 IBISML2022-28 pp.193-198 |
| HWS | 2022-04-26 11:20 |
Tokyo | AIST Tokyo Waterfront (Annex) (Primary: On-site, Secondary: Online) |
Deep Learning-based Side-Channel Attacks against Software-Implemented RSA using Binary Exponentiation with Dummy Multiplication Seiya Shimada, Kunihiro Kuroda, Yuta Fukuda, Kouta Yoshida, Takeshi Fujino (Ritsumeikan Univ.) HWS2022-3 |
Recently, deep learning-based side-channel attacks (DL-SCA) against symmetric key cryptography such as AES have been rep... [more] | HWS2022-3 pp.13-18 |
| MSS, NLP | 2022-03-28 15:45 |
Online | Online | Analysis on development process of neural networks with different internal states Sho Shimizu, Hideyuki Kato (Oita Univ.) MSS2021-67 NLP2021-138 |
It has been reported that fluctuations have positive effects, are extensively studied, in neuronal computation and infor... [more] | MSS2021-67 NLP2021-138 pp.61-66 |
| MSS, NLP | 2022-03-29 09:40 |
Online | Online | Effects of sparse connections in spiking neural networks for unsupervised pattern recognition Hiroki Shinagawa, Kantaro Fujiwara, Gouhei Tanaka (Univ. of Tokyo) MSS2021-69 NLP2021-140 |
Recently, the spiking neural network (SNN) models, which compute using spatio-temporal information representation by neu... [more] | MSS2021-69 NLP2021-140 pp.71-76 |
| IE, ITS, ITE-AIT, ITE-ME, ITE-MMS [detail] | 2022-02-21 11:30 |
Online | Online | ITS2021-28 IE2021-37 |
The dynamic range of electronic imaging is orders of magnitudes smaller than that of human vision. To obtain images of h... [more] | ITS2021-28 IE2021-37 pp.19-24 |
| SR | 2022-01-25 14:40 |
Online | Online | Performance Evaluation of Access Control and Transmission Datarate Adaptation using Redundant Check Information for IEEE 802.11ax Wireless LAN Kazuto Yano, Kenta Suzuki, Babatunde Ojetunde (ATR), Koji Yamamoto (Kyoto Univ.) SR2021-81 |
In order to meet increasing traffic load on wireless communication, the authors have conducted research and development ... [more] | SR2021-81 pp.103-110 |
| ISEC | 2021-05-19 15:30 |
Online | Online | [Invited Talk]
Simple Electromagnetic Analysis Against Activation Functions of Deep Neural Networks (from AIHWS 2020) Go Takatoi, Takeshi Sugawara, Kazuo Sakiyama (UEC), Yuko Hara-Azumi (Tokyo Tech), Yang Li (UEC) ISEC2021-9 |
This invited abstract is based on the papers [1] and [2]. There are physical attacks such as side-channel attacks that a... [more] | ISEC2021-9 p.34 |
| LOIS, IPSJ-SPT, IPSJ-CN | 2021-05-11 11:25 |
Online | Online | Analysis of behaviors by students in cooperative learning for video lectures (Fifth report) Eiji Watanabe (Konan Univ.), Takashi Ozeki (Fukuyama Univ.), Takeshi Kohama (Kindai Univ.) LOIS2021-11 |
In this report, we propose a model for evaluating the interaction between behaviors of students and quantify the strengt... [more] | LOIS2021-11 pp.60-65 |
| SIP, IT, RCS | 2021-01-22 09:50 |
Online | Online | Selection of Interference Cancellation Technique Using Decision Trees for Uplink Non-orthogonal Multiple Access
-- Evaluation of Communication Success Rate in A Mobile Environment -- Noriaki Yamamoto (Meiji Univ.), Masafumi Moriyama, Kenichi Takizawa (NICT), Tetsushi Ikegami (Meiji Univ.) IT2020-85 SIP2020-63 RCS2020-176 |
As IoT（Internet of Things）develops, wireless access techniques that can effectively accommodate massive number of device... [more] | IT2020-85 SIP2020-63 RCS2020-176 pp.119-124 |
| RCS, AP, UWT (Joint) |
2020-11-25 09:50 |
Online | Online | Deep Learning Aided Channel Estimation for Massive MIMO with Pilot Contamination Hiroki Hirose, Tomoaki Ohtsuki (Keio Univ.) RCS2020-110 |
In a time division duplex (TDD) based massive multiple-input multiple-output (MIMO) system, a base station (BS) needs ac... [more] | RCS2020-110 pp.1-6 |
| HWS, ICD [detail] | 2019-11-01 16:00 |
Osaka | DNP Namba SS Bld. | A Study of Hardware Trojan Detection Method using Deep Learning in Asynchronous Circuits Hikaru Inafune, Masashi Imai (Hirosaki Univ.) HWS2019-63 ICD2019-24 |
There are typically two timing methods in VLSI designs known as synchronous circuits which use a global clock and async... [more] |
HWS2019-63 ICD2019-24 pp.35-40 |
| ASN, ICTSSL | 2018-05-15 11:50 |
Hiroshima | Hiroshima City Univ. | Study of Automatic Landslide Disaster Danger Level Determination Method by Image Processing on Deep Learning Yusuke Ota, Koichi Shin, Masahiro Nishi (Hiroshima City Univ.) ICTSSL2018-13 ASN2018-13 |
In order to reduce damages caused by landslide disasters, it is important to create an environment in which residents ju... [more] | ICTSSL2018-13 ASN2018-13 pp.71-76 |
| LOIS | 2018-03-01 10:00 |
Okinawa | Naha-City IT Souzoukan(Okinawa) | A Method of Automatic Training Data Collection for Office Worker Seated-State using Machine Learning Daisuke Ikeda, Yukihiro Tsuboshita, Takeshi Onishi (Fuji Xerox) LOIS2017-71 |
Nowadays, approximately 75% of all employees in industrial countries are required to work in a seated position. Accordin... [more] | LOIS2017-71 pp.1-5 |
| LOIS, ISEC, SITE | 2017-11-10 11:00 |
Kyoto | Estimation of Office Worker Seated-State with Ambient Sensors Daisuke Ikeda, Yukihiro Tsuboshita, Takeshi Onishi (Fuji Xerox) ISEC2017-63 SITE2017-45 LOIS2017-40 |
Nowadays, approximately 75% of all employees in industrial countries are required to work in a seated position. Long-ter... [more] | ISEC2017-63 SITE2017-45 LOIS2017-40 pp.87-91 |
|
| MBE, NC (Joint) |
2017-03-13 10:25 |
Tokyo | Kikai-Shinko-Kaikan Bldg. | Estimation of the change of agent's behavior strategy using state-action history Shihori Uchida, Shigeyuki Oba, Shin Ishii (Kyoto Univ.) NC2016-65 |
Reinforcement learning (RL) is a model of learning process of animals and intelligent agents to obtain the optimal behav... [more] | NC2016-65 pp.7-12 |
| CCS | 2016-11-04 11:15 |
Kyoto | Kyoto Sangyo Univ. (Musubiwaza Bldg.) | Unsupervised Learning with Spike-Timing Dependent Delay Learning Model Takashi Matsubara (Kobe Univ.) CCS2016-32 |
Precious timing of neuronal spikes is considered to play an important role in signal transmission and processing in cent... [more] | CCS2016-32 pp.13-16 |
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