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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 10 of 10  /   
Committee Date Time Place Paper Title / Authors Abstract Paper #
IBISML 2024-12-20
10:30
Hokkaido Lecture room 1 (D101), Graduate School of Environmental Science (Hokkaido, Online)
(Primary: On-site, Secondary: Online)
Training Deep Neural Networks for Fast Data Assimilation
Yuta Ono (UTokyo), Yuta Tarumi, Keisuke Fukuda, Shin-ichi Maeda (PFN) IBISML2024-36
Data assimilation (DA) is imperative to achieve accurate state estimation from observations and numerical simulations. A... [more] IBISML2024-36
pp.34-40
R 2024-05-18
15:00
Aichi Nagoya Champus, Aichi University (Aichi, Online)
(Primary: On-site, Secondary: Online)
Reliability Prediction in Software Unit Test
Keisuke Fukuda, Tadashi Dohi, Hiroyuki Okamura (Hiroshima Univ.) R2024-4
Software bug prediction aims at predicting bug-prone modules in advance during the unit testing, and is reduced to a sta... [more] R2024-4
pp.17-22
MI 2022-01-26
10:39
Online Online (Online) [Short Paper] Counting of alveoli in synchrotron radiation 3D CT images using U-Net
Keisuke Fukuda, Kurumi Saito, Yoshiki Kawata (Tokushima Univ.), Keiji Umetani (JASRI), Yasutaka Nakano (Shiga Med Univ), Hiroaki Sakai (AGMC), Toshihiro Okamoto (Cleveland Clinic), Noboru Niki (Medical Science Institute Inc.) MI2021-55
 [more] MI2021-55
pp.45-46
MI 2021-08-27
14:35
Online Online (Online) [Short Paper] Three-dimensional structural analysis of alveolar groups using large-field synchrotron radiation micro CT
Kurumi Saito, Keisuke Fukuda, Yoshiki Kawata (Tokushima Univ), Keiji Umetani (JASRI), Yasutaka Nakano (Shiga Med Univ), Hiroaki Sakai (AGMC), Toshihiro Okamoto (Cleveland Clinic), Noboru Niki (Medical science Institute, Inc.) MI2021-23
Three-dimensional microstructural analysis of the lung is useful for precise understanding of lung growth and disease pr... [more] MI2021-23
pp.8-9
R 2021-07-17
14:25
Online Virtual (Online) Refined Ensemble Learning Algorithms for Software Bug Prediction -- Metaheuristic Approach --
Keisuke Fukuda, Tadashi Dohi, Hiroyuki Okamura (Hiroshima Univ.) R2021-19
In this paper, we propose to apply three metaheuristic algorithms; latin hypercube sampling, ABC (artificial
bee colon... [more]
R2021-19
pp.18-23
MI 2021-03-16
15:15
Online Online (Online) [Short Paper] Three-dimensional analysis of alveolar construction using synchrotron radiation CT with a large-field microscope
Kurumi Saito, Keisuke Fukuda, Yoshiki Kawata, Noboru Niki (Tokushima Univ), Keiji Umetani (JASRI), Yasutaka Nakano (Shiga Univ. of Med. Sci.), Hiroaki Sakai (AGMC), Toshihiro Okamoto (Cleveland Clinic) MI2020-78
Conversion of images at micro level of the normal lung and those with very early stage lung disease, and the quantitativ... [more] MI2020-78
pp.134-135
NC, MBE
(Joint)
2021-03-05
10:20
Online Online (Online) On an online learning rule for reservoir neural network hardware
Kaito Kudo, Keisuke Fukuda, Yoshihiko Horio (Tohoku Univ.) NC2020-66
 [more] NC2020-66
pp.133-138
NLP, NC
(Joint)
2020-01-25
09:50
Okinawa Miyakojima Marine Terminal (Okinawa) Quantitative Evaluation of Dynamics in Chaotic Neural Network Reservoir
Keisuke Fukuda, Maakito Inoue, Yoshihiko Horio (Tohoku Univ.) NLP2019-102
A chaotic neural network reservoir has been proposed as a method to introduce diversity in reservoir neural network dyna... [more] NLP2019-102
pp.89-94
NLP, NC
(Joint)
2020-01-25
10:10
Okinawa Miyakojima Marine Terminal (Okinawa) Application of Chaotic Neural Network Reservoir to Speech Recognition
Maakito Inoue, Keisuke Fukuda, Yoshihiko Horio (Tohoku Univ.) NLP2019-103
The neural network reservoir is a learning network model using the recurrent neural network. The chaotic neural network ... [more] NLP2019-103
pp.95-98
EMD 2014-03-07
14:05
Kanagawa Yokohama Nat'l Univ. (Kanagawa) The simulation a different metal configuration changes in multi-point
Eisuke Enomoto, Yu Kodama, Keisuke Fukuda, Yusuke Yanagi, Yoshitada Watanabe, Masaomi Arai (Kogakuin Univ) EMD2013-153
(To be available after the conference date) [more] EMD2013-153
pp.17-20
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