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 Results 1 - 13 of 13  /   
Committee Date Time Place Paper Title / Authors Abstract Paper #
EMM, BioX, ISEC, SITE, ICSS, HWS, IPSJ-CSEC, IPSJ-SPT [detail] 2023-07-25
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
IE, ITS, ITE-MMS, ITE-ME, ITE-AIT [detail] 2023-02-21
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
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
IBISML 2022-01-17
Online Online Automatic Makeup Transfer with GANs and Its Quantitative Evaluation
Cuilin Wang, Jun'ichi Takeuchi (Kyushu Univ.) IBISML2021-20
Transferring makeup from a reference image with makeup to a source image without makeup has a wide range of application ... [more] IBISML2021-20
IMQ 2021-10-22
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
Online Online Visualization of CNNs using Preferred Stimulus in Receptive Fields
Genta Kobayashi, Hayaru Shouno (UEC) NC2020-47
Convolutional neural networks have shown high performance at image processing task, and
they are interpreted by variou... [more]
MI 2019-01-23
Okinawa   Segmentation for diffuse lung disease opacities on CT images using U-Net and residual U-Net
Kanako Murakami, Shoji Kido, Yasushi Hirano, Shingo Mabu (Yamaguchi Univ.), Kenji Kondo (AIST/Panasonic), Jun Ozawa (AIST) MI2018-102
Segmentation is important for diagnosis of diffuse lung diseases (DLD) as same as classification. In recent years, a lot... [more] MI2018-102
Okinawa Okinawa Industry Support Center A simple evaluation method of residual aberration in reflect arrays
Aoi Kotoura, Shigeru Makino, Yoshimi Sunaga (KIT), Michio Takikawa, Hiromasa Nakajima (Mitsubishi Electric) AP2018-132
In the conventional method of evaluating the phase error frequency characteristic, the relationship between the phase er... [more] AP2018-132
IE 2018-06-29
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
SANE 2017-08-24
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
PRMU, IBISML, IPSJ-CVIM [detail] 2015-09-15
Ehime   Image-based Face Modeling from Few Images Using Augmented Eigenface
Hisayoshi Chugan, Tsuyoshi Fukuda, Takeshi Shakunaga (Okayama Univ.) PRMU2015-87 IBISML2015-47
A real-time face tracking and recognition system was proposed by Oka and Shakunaga [1], [2]. In their system, 24 images ... [more] PRMU2015-87 IBISML2015-47
PRMU, MVE, IPSJ-CVIM [detail] 2011-01-21
Shiga   High Frequency Compensated Face Hallucination Method
So Sasatani, Xian-Hua Han, Motonori Ohashi, Yutaro Iwamoto, Yen-Wei Chen (Ritsumeikan Univ.) PRMU2010-189 MVE2010-114
Face Hallucination method is one of learning-based super-resolution techniques, which can reconstruct a high-resolution ... [more] PRMU2010-189 MVE2010-114
EID, ITE-IDY 2009-07-23
Tokyo Kikai-Shinko-Kaikan Bldg. Analysis of Impurity Ion Affecting Image Sticking Effect on Liquid Crystal Display
Masanobu Mizusaki, Tetsuya Miyashita, Tatsuo Uchida (Tohoku Univ.), Yuichiro Yamada (Sharp. Corp.) EID2009-15
Image sticking can be observed in some case and it degrades the image quality of liquid crystal (LC) display. The image... [more] EID2009-15
 Results 1 - 13 of 13  /   
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