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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 15 of 15  /   
Committee Date Time Place Paper Title / Authors Abstract Paper #
NC, MBE
(Joint)
2024-03-12
14:45
Tokyo The Univ. of Tokyo
(Primary: On-site, Secondary: Online)
Visualization of the learning process of ResNet revealing its learning dynamics
Ryodo Yuge, Takashi Shinozaki (Kindai Univ.) NC2023-59
We visualize the impact of skip connections, a key element in residual networks (ResNet), and visualize its impact on th... [more] NC2023-59
p.94
EMM, BioX, ISEC, SITE, ICSS, HWS, IPSJ-CSEC, IPSJ-SPT [detail] 2023-07-25
09:00
Hokkaido Hokkaido Jichiro Kaikan CNN-Based Iris Recognition Using Multi-spectral Iris Images
Ryosuke Kuroda, Tetsuya Honda, Hironobu Takano (Toyama Prefectural Univ.) ISEC2023-36 SITE2023-30 BioX2023-39 HWS2023-36 ICSS2023-33 EMM2023-36
Iris recognition using a near-infrared camera is generally known as a biometric authentication method with high accuracy... [more] ISEC2023-36 SITE2023-30 BioX2023-39 HWS2023-36 ICSS2023-33 EMM2023-36
pp.147-151
IE, ITS, ITE-MMS, ITE-ME, ITE-AIT [detail] 2023-02-21
15:45
Hokkaido Hokkaido Univ. A Residual U-Net Architecture for Shuttlecock Detection
Muhammad Abdul Haq (TMU), Shuhei Tarashima (NTT Com), Norio Tagawa (TMU)
Detection of fast-moving shuttlecocks is essential for badminton video analysis. Several methods based on deep learning ... [more]
SIP, BioX, IE, MI, ITE-IST, ITE-ME [detail] 2022-05-20
17:00
Kumamoto Kumamoto University Kurokami Campus
(Primary: On-site, Secondary: Online)
Deformable registration of 3D medical images with Deep Residual UNet
Taiga Nakamura, Yuki Sato, Hiroyuki Kudo, Hotaka Takizawa (Univ. of Tsukuba) SIP2022-30 BioX2022-30 IE2022-30 MI2022-30
(To be available after the conference date) [more] SIP2022-30 BioX2022-30 IE2022-30 MI2022-30
pp.156-160
MBE, NC
(Joint)
2021-10-29
11:40
Online Online A numerical study on the relationship between complexity and accuracy of neural networks based on ordinary differential equations
Kaoru Esashika, Jun Ohkubo (Saitama Univ.) NC2021-26
In recent years, many reports have been published on deep neural networks. The residual networks have contributed to rem... [more] NC2021-26
pp.46-50
IMQ 2021-10-22
13:45
Osaka Osaka Univ. A Tiny Convolutional Neural Network for Image Super-Resolution
Kazuya Urazoe, Nobutaka Kuroki, Yu Kato, Shinya Ohtani (Kobe Univ.), Tetsuya Hirose (Osaka Univ.), Masahiro Numa (Kobe Univ.) IMQ2021-7
This paper surveys three techniques for reducing computational costs of convolutional neural network (CNN) for image sup... [more] IMQ2021-7
pp.2-7
ET 2021-09-10
13:15
Online Online Predicting Code Reading Test Answers by Using Eye Movement Features
YUE YAN, Minoru Nakayama (Tokyo Tech) ET2021-11
Code reading comprehension progress has been shown to distribute in the eye movement data, which makes predict the code ... [more] ET2021-11
pp.17-22
IBISML 2021-03-03
11:15
Online Online IBISML2020-46 Developing a profitable trading strategy is a central problem in the financial industry. In this presentation, we develo... [more] IBISML2020-46
p.38
ITE-HI, IE, ITS, ITE-MMS, ITE-ME, ITE-AIT [detail] 2020-02-27
14:15
Hokkaido Hokkaido Univ.
(Cancelled but technical report was issued)
A note on detection of distress regions in subway tunnels by using U-net based network
An Wang, Ren Togo, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ)
This paper presents an automated distress region detection method using subway tunnel images. We previously proposed a m... [more]
ITS, IE, ITE-MMS, ITE-HI, ITE-ME, ITE-AIT [detail] 2019-02-20
13:00
Hokkaido Hokkaido Univ. A note on automatic malignant tumor candidate detection based on a 3D deep residual network with FDG-PET/CT images
Zongyao Li, Ren Togo, Takahiro Ogawa, Kenji Hirata, Osamu Manabe, Tohru Shiga, Miki Haseyama (Hokkaido Univ.)
In this paper, we propose a malignant tumor candidate detection method with FDG-PET/CT images. We design our network bas... [more]
IE 2018-06-29
10:20
Okinawa   Single-image Rain Removal Using Residual Deep Learning
Takuro Matsui, Masaaki Ikehara, Takanori Fujisawa (Keio Univ.) IE2018-23
Most outdoor vision systems can be influenced by rainy weather conditions. In this paper, we address a rain removal prob... [more] IE2018-23
pp.13-18
PRMU, MI, IE, SIP 2018-05-18
10:15
Gifu   Electronic Cleansing for CT Colonography using Deep Learning
Rie Tachibana (NIT, Oshima College), Janne J. Nappi, Toru Hironaka, Hiroyuki Yoshida (MGH/HMS) SIP2018-8 IE2018-8 PRMU2018-8 MI2018-8
Although colonoscopy is considered as a standard procedure for colon cancer screening, CT colonography (CTC) has recentl... [more] SIP2018-8 IE2018-8 PRMU2018-8 MI2018-8
pp.35-37
PRMU 2017-10-12
13:30
Kumamoto  
Yoshihiro Yamada, Masakazu Iwamura, Koichi Kise (Osaka Pref. Univ.) PRMU2017-72
(To be available after the conference date) [more] PRMU2017-72
pp.55-60
SANE 2017-08-24
13:50
Osaka OIT UMEDA Campus Deep Learning for Target Classification from SAR Imagery -- Data Augmentation and Translation Invariance --
Hidetoshi Furukawa (Toshiba Infrastructure Systems & Solutions) SANE2017-30
This report deals with translation invariance of convolutional neural networks (CNNs) for automatic target recognition (... [more] SANE2017-30
pp.13-17
PRMU, CNR 2017-02-18
10:55
Hokkaido   PRMU2016-158 CNR2016-25 (To be available after the conference date) [more] PRMU2016-158 CNR2016-25
pp.35-40
 Results 1 - 15 of 15  /   
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