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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
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Committee Date Time Place Paper Title / Authors Abstract Paper #
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
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
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]
PRMU, IBISML, IPSJ-CVIM [detail] 2023-03-02
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
NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] 2022-06-29
(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
HWS 2022-04-26
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
MSS, NLP 2022-03-28
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
MSS, NLP 2022-03-29
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
IE, ITS, ITE-AIT, ITE-ME, ITE-MMS [detail] 2022-02-21
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
SR 2022-01-25
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
ISEC 2021-05-19
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
LOIS, IPSJ-SPT, IPSJ-CN 2021-05-11
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
SIP, IT, RCS 2021-01-22
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
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
HWS, ICD [detail] 2019-11-01
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
ASN, ICTSSL 2018-05-15
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
LOIS 2018-03-01
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
LOIS, ISEC, SITE 2017-11-10
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
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
CCS 2016-11-04
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
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