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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 53  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
EMCJ 2023-11-24
13:25
Tokyo Kikai-Shinko-Kaikan
(Primary: On-site, Secondary: Online)
A Study on Explainability of Convolutional Neural Network Predicting Electric Characteristics of Automotive Wire Harness Based on Score Regression Activation Mapping (Score-RAM)
Syumpei Ebina, Tadatoshi Sekine, Shin Usuki, Kenjiro T. Miura (Shizuoka Univ.) EMCJ2023-74
In this report, we propose score regression activation mapping (Score-RAM) based on explainable artificial intelligence.... [more] EMCJ2023-74
pp.13-18
MW, EMCJ, EST, IEE-EMC [detail] 2023-10-19
09:00
Yamagata Yamagata University
(Primary: On-site, Secondary: Online)
A Study on Coaxial-Probe-Based Measurement Method for EM-parameters of Absorbers on a Cylinder Surface
Sho Kato, Chun-Ping Chen, Takaharu Hiraoka, Tetsuo Anada (Kanagawa Univ.) EMCJ2023-35 MW2023-89 EST2023-62
With the development of wireless communication technology, a wide range of objects can be connected to the Internet, fac... [more] EMCJ2023-35 MW2023-89 EST2023-62
pp.1-6
NC, NLP 2023-01-29
15:55
Hokkaido Future University Hakodate
(Primary: On-site, Secondary: Online)
Indoor air quality prediction using multi-reservoir echo state network with attention mechanism
Wenrui Qiu, Gouhei Tanaka (UTokyo) NLP2022-106 NC2022-90
Indoor air quality (IAQ) is a critical matter of concern in terms of its impact on public health and well-being. Researc... [more] NLP2022-106 NC2022-90
pp.135-140
EMT, IEE-EMT 2022-11-18
13:25
Tokyo Kikai-Shinko-Kaikan Bldg.
(Primary: On-site, Secondary: Online)
[Invited Lecture] On Electromagnetic Field Simulation Using Physics-Informed Deep Learning
Kazuhiro Fujita (Saitama IT) EMT2022-59
Physical laws appeared in the fields of physics and engineering can be described by partial differential equations in ma... [more] EMT2022-59
pp.85-88
PN 2022-08-29
09:55
Hokkaido
(Primary: On-site, Secondary: Online)
Comparison of overfitting in ANN- and VSTF-based nonlinear equalizers to repeated random bit patterns
Kai Ikuta, Nakamura Jinya, Motai Daisuke, Nakamura Moriya (Meiji Univ.) PN2022-9
We compared the overfitting characteristics of artificial-neural-network- (ANN-) and Volterra-series-transfer-function- ... [more] PN2022-9
pp.5-9
CS 2022-07-15
14:50
Kagoshima Yakushima Environmental and Cultural Village Center
(Primary: On-site, Secondary: Online)
[Invited Talk] Optical Eigenvalue Demodulation Using Complex Moment-based Eigenvalue Solver
Yuhei Terashi, Daisuke Hisano, Ken Mishina (Osaka Univ.), Yuki Yoshida (NICT), Akihiro Maruta (Osaka Univ.) CS2022-37
Optical eigenvalue modulation has been attracting attention as an ideal modulation not affected by chromatic dispersion ... [more] CS2022-37
pp.104-109
VLD, HWS [detail] 2022-03-07
15:05
Online Online Low-Energy and Fast Inference Method for Spiking Neural Networks Using Dynamic Threshold Adjustment
Takehiro Habara, Hiromitsu Awano (Kyoto Univ.) VLD2021-87 HWS2021-64
Conventional SNNs have fixed thresholds that determine the possibility of neuron firing, resulting in degradation of inf... [more] VLD2021-87 HWS2021-64
pp.57-62
OCS, CS
(Joint)
2022-01-13
14:05
Yamaguchi Conference room 204A・B at KDDI Ishin-hall
(Primary: On-site, Secondary: Online)
Impact of Range of Eigenvalue Extraction on Demodulation Method using Complex Moment-based Eigenvalue Solver
Yuhei Terashi, Daisuke Hisano, Ken Mishina (Osaka University), Yuki Yoshida (NICT/Osaka University), Akihiro Maruta (Osaka University) CS2021-68
Optical eigenvalue modulation has been attracting attention as an ideal modulation not affected by chromatic dispersion ... [more] CS2021-68
pp.1-6
PRMU 2021-12-16
16:45
Online Online Supervoxel-based Explanation for Action Recognition
Ying Ji (Nagoya Univ.), Yu Wang (Ritsumeikan Univ.), Kensaku Mori (Nagoya Univ.), Jien Kato (Ritsumeikan Univ.) PRMU2021-42
Deep neural network has shown remarkable performance in various areas, including image classification, action recognitio... [more] PRMU2021-42
pp.98-100
CPSY, DC, IPSJ-SLDM, IPSJ-EMB, IPSJ-ARC [detail] 2021-03-26
11:00
Online Online An Estimation Method of a Defect Types for Suspected Fault Lines in Logical Faulty VLSI Using Neural Networks
Natsuki Ota, Toshinori Hosokawa (Nihon Univ.), Koji Yamazaki (Meiji Univ.), Yukari Yamauchi, Masayuki Arai (Nihon Univ.) CPSY2020-61 DC2020-91
Since fault diagnosis methods for specified fault models might cause misprediction and non-prediction, a fault diagnosis... [more] CPSY2020-61 DC2020-91
pp.67-72
SIS 2021-03-04
15:50
Online Online [Invited Talk] A Proposal in Order to use AI Safely for Control
Nobuyasu Kanekawa (Hitachi) SIS2020-50
The research of the deep learning which developed the "neural Network" proposed by the second AI (artificial intelligenc... [more] SIS2020-50
pp.83-87
PN 2021-03-01
14:55
Online Online [Invited Lecture] CFO estimation in eigenvalue-domain and its application to neural network-based demodulation for eigenvalue-modulated signal
Ken Mishina, Takaya Maeda (Osaka Univ.), Yuki Yoshida (NICT), Daisuke Hisano, Akihiro Maruta (Osaka Univ.) PN2020-45
An eigenvalue-domain (ED) artificial neural network (ANN)-based demodulation method for eigenvalue-modulated signals has... [more] PN2020-45
pp.20-25
IA 2020-10-01
11:15
Online Online Malicious URLs Detection Using an Integrated AI Framework
Bo-Xiang Wang, Ren-Feng Deng, Yi-Wei Ma, Jiann-Liang Chen (NTUST) IA2020-1
Malicious attacks on computer networks are quite common, and the internet attacks are even more widespread, such as Malv... [more] IA2020-1
pp.1-5
SCE 2020-01-17
13:15
Kanagawa   [Poster Presentation] Investigation of logic gate using bi-directionally-coupled quantum flux parametron array
Kohei Miyake, Yuki Yamanashi, Nobuyuki Yoshikawa (Yokohama Natl. Univ.) SCE2019-59
We study a bi-directionally-coupled quantum-flux-parametron (QFP) array as a new configuration method of a superconducti... [more] SCE2019-59
pp.121-124
NC, MBE 2019-12-06
10:10
Aichi Toyohashi Tech Implementation of Cerebellar Spiking Neural Network Model on a FPGA
Yusuke Shinji (Chubu Univ.), Hirotsugu Okuno (OIT), Yutaka Hirata (Chubu Univ.) MBE2019-46 NC2019-37
The cerebellum is crucially involved in motor control and learning. Its neuronal network architecture and firing propert... [more] MBE2019-46 NC2019-37
pp.7-12
RISING
(2nd)
2019-11-26
10:30
Tokyo Fukutake Learning Theater, Hongo Campus, Univ. Tokyo [Poster Presentation] Application of Machine Learning to Optical Eigenvalue Communication
Ken Mishina, Shohei Yamamoto (Osaka Univ.), Yuki Yoshida (NICT), Daisuke Hisano, Akihiro Maruta (Osaka Univ.)
Development and innovations of transmission technology that will increase the transmission capacity of optical communica... [more]
OCS, PN, NS
(Joint)
2019-06-20
13:00
Iwate MALIOS(Morioka) Overestimation of Artificial Neural Network and Volterra Series Transfer Function in PRBS Based Signal Quality Evaluation
Kai Ikuta, Yuta Otsuka, Yuta Fukumoto, Moriya Nakamura (Meiji Univ.) OCS2019-13
We compared overestimation problem of Volterra series transfer function (VSTF) with that of artificial neural network (A... [more] OCS2019-13
pp.17-20
SDM, ED, CPM 2019-05-16
16:15
Shizuoka Shizuoka Univ. (Hamamatsu) Evaluation of switching characteristics of Ta2O5-δ based analog resistive memory using Cu and Ta top electrode
Yuanlin Li, Atsushi Tsurumaki-Fukuchi, Masashi Arita (Hokkaido Univ.), Takashi Morie (Kyushu Inst. Tech.), Yasuo Takahashi (Hokkaido Univ.) ED2019-16 CPM2019-7 SDM2019-14
We present the differences of two mechanisms’ initial states and multilevel switching behavior using Ta2O5-δ ReRAM. For ... [more] ED2019-16 CPM2019-7 SDM2019-14
pp.29-34
MoNA 2018-12-25
14:00
Tokyo   Emotions detection scheme using facial skin temperature and heart rate
Kahil Mustafa Jamal S, Eiji Kamioka (SIT) MoNA2018-47
The main aim of this study is to detect emotions based on facial skin temperature and Heart Rate (HR) Using thermals cam... [more] MoNA2018-47
pp.49-54
QIT
(2nd)
2018-11-26
13:30
Tokyo The University of Tokyo [Poster Presentation] Quantum Algorithm for Supervised Deep Learning
Yasuhito Kawano (NTT), Hiroshi Sekigawa (TUS)
The estimation problem of weights of a feed-forward neural network can be regarded as the problem of solving linear equa... [more]
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