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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 30  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
CQ, MIKA
(Joint)
(2nd)
2023-08-31
10:50
Fukushima Tenjin-Misaki Sports Park [Poster Presentation] An Exploration of a Graph Super-Resolution Algorithm using Spectra and Degree Distributionof a Graph Super-Resolution Algorithm using Spectra and Degree Distribution
Hiroyoshi Sawano (Kwansei Gakuin Univ), Ryotaro Matsuo (Fukuoka Univ), Hiroyuki Ohsaki (Kwansei Gakuin Univ)
Generally, for large-scale and complex networks, obtaining information on the entire topology is not straightforward due... [more]
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
MI 2021-05-17
14:40
Online Online MR super-resolution based on signal-image domain learning using phase scrambling Fourier transform imaging
Kazuki Yamato, Hiromichi Wakatsuki, Satoshi Ito (Utsunomiya Univ.) MI2021-6
In the phase-scrambling Fourier transform (PSFT) imaging, the signals not sampled during imaging can be extrapolated and... [more] MI2021-6
pp.14-19
MICT, MI 2020-11-04
15:50
Online Online [Short Paper] An Experimental Study on Color Laparoscopic High-Definition Video Quality Assessment Including Super-resolution
Norifumi Kawabata (Tokyo Univ. of Science), Toshiya Nakaguchi (Chiba Univ.) MICT2020-19 MI2020-45
After considering medical image analysis support, it is one of importance factors to assess high-definition image qualit... [more] MICT2020-19 MI2020-45
pp.60-61
ITE-HI, IE, ITS, ITE-MMS, ITE-ME, ITE-AIT [detail] 2020-02-27
16:35
Hokkaido Hokkaido Univ.
(Cancelled but technical report was issued)
A Study on Region Segmentation of Color Laparoscopic Images after Contrast Enhancement Including Super-Resolution CNN by Image Regions
Norifumi Kawabata (Tokyo Univ. of Science), Toshiya Nakaguchi (Chiba Univ.)
As one of image pre-processing method to detect, recognize, and estimate lesion or characteristic region in medical imag... [more]
IE 2019-06-21
13:00
Okinawa   SUPER-RESOLUTION BASED ON BACK-PROJECTION OF INTERPOLATED IMAGE
Sawiya Kiatpapan, Takuro Yamaguchi, Masaaki Ikehara (Keio Univ.) IE2019-17
Image upscaling to obtain high quality digital image is one of the active research topics as it is applicable in the con... [more] IE2019-17
pp.1-5
IBISML 2019-03-06
13:00
Tokyo RIKEN AIP Magnetic Resonance Angiography Image Restoration by Super Resolution based on Deep Learning
Shizen Kitazaki, Masanori Kawakita, Yutaka Jitumatu (Kyushu Univ.), Shigehide Kuhara (Kyorin Univ.), Akio Hiwatashi, Jun'ichi Takeuchi (Kyushu Univ.) IBISML2018-114
Magnetic Resonance Imaging (MRI) is one of the powerful techniques to acquire in vivo information. However, to obtain a ... [more] IBISML2018-114
pp.65-72
PN, EMT, OPE, EST, MWP, LQE, IEE-EMT [detail] 2019-01-18
14:45
Osaka Osaka University Nakanoshima Center Super-resolution for GPR Images by Deep Learning Using Generative Adversarial Networks
Jun Sonoda (NIT, Sendai), Tomoyuki Kimoto (NIT, Oita) PN2018-75 EMT2018-109 OPE2018-184 LQE2018-194 EST2018-122 MWP2018-93
Recently, deterioration of social infrastructures such as tunnels and bridges become a serious social problem. It is req... [more] PN2018-75 EMT2018-109 OPE2018-184 LQE2018-194 EST2018-122 MWP2018-93
pp.237-242
IMQ 2018-05-25
14:15
Chiba Chibe Institute of Technology, Tsudanuma Campus Optimal Design and Coded Image Quality Assessment of the Multi-view and Super-resolution Images Based on Structure of Convolutional Neural Network
Norifumi Kawabata (Nagoya Univ.) IMQ2018-3
The image screen resolution by viewpoints is low, comparing to single-view images since there are many viewpoints for mu... [more] IMQ2018-3
pp.15-20
IE 2016-07-01
14:40
Okinawa   Subjective assessment of Super-Resolution on 4K-TV -- Performance of Learning-Based Super-Resolution and Non-Linear Signal Processing --
Hiroki Shoji, Seiichi Gohshi (Kogakuin Univ.) IE2016-43
4K television (TV) has become common in the market and the prices have become reasonable. Most of 4K TV sets are equippe... [more] IE2016-43
pp.43-48
EA, SP, SIP 2016-03-29
09:00
Oita Beppu International Convention Center B-ConPlaza [Poster Presentation] Examination of Acoustic Sensing Using Super-directivity Speaker and Super-resolution Signal Processing
Yuya Asakura, Kan Okubo, Norio Tagawa (Tokyo Met. Univ.) EA2015-117 SIP2015-166 SP2015-145
Acoustic sensing technology in the air is a promising method to acquire shapes and/or position of a targetobject. Univer... [more] EA2015-117 SIP2015-166 SP2015-145
pp.283-286
SANE 2015-11-23
14:50
Overseas AIT, Bangkok, Thailand Super-Resolution Time of Arrival Estimation Using Random Resampling in Compressed Sensing
Masanari Noto, Fang Shang, Shouhei Kidera, Tetsuo Kirimoto (UEC) SANE2015-54
Super-resolution time of arrival (TOA) estimation techniques are strongly demanded for general radar system. As one of t... [more] SANE2015-54
pp.27-32
IE 2015-06-19
10:20
Okinawa Okinawa Cellular Subjective Assessment of 4K Videos -- Application of Super-Resolution with Nonlinear Signal Processing to 4K Displays --
Chinatsu Mori, Masaki Sugie, Hirohisa Takeshita, Seiichi Gohshi (Kogakuin Univ.) IE2015-41
Results of a subjective assessment of super-resolution (SR) technology for 4K TV sets are reported. 4K TV sets are curre... [more] IE2015-41
pp.51-55
SIP, EA, SP 2015-03-03
09:00
Okinawa   [Poster Presentation] MSIST-based Image Restoration with Non-separable Oversampled Lapped Transforms
Sho Wakasugi, Shogo Muramatsu (Niigata Univ) EA2014-90 SIP2014-131 SP2014-153
This work proposes, an image restoration technique with modified subbsnd-adaptive iterative shrinkage thresholding (MSIS... [more] EA2014-90 SIP2014-131 SP2014-153
pp.91-96
US 2015-02-27
11:30
Kanagawa IHI Yokohama Efficient Realization of Super Resolution FM-Chirp Correlation Method Using Synthetic Aperture Scheme
Takayuki Wada, Kan Okubo, Norio Tagawa (Tokyo Metro. Univ.), Yoshiyasu Hirose (ITOCHU Techno-Solutions Corp.) US2014-97
This study addresses the efficient realization of super resolution FM-chirp correlation method (SCM) using synthetic ape... [more] US2014-97
pp.19-22
IE, ICD, VLD, IPSJ-SLDM [detail] 2014-10-03
09:55
Miyagi   Subjective assessment of super-resolution -- Paired comparison with 4K TV --
Masaki Sugie, Seiichi Gohshi, Hirohisa Takeshita, Chinatsu Mori (Kogakuin Univ.) VLD2014-69 ICD2014-62 IE2014-48
In this paper subjective assessment results of super-resolution (SR) technologies for 4K TV sets are reported. 4K TV set... [more] VLD2014-69 ICD2014-62 IE2014-48
pp.51-56
NC, MBE
(Joint)
2014-03-18
14:20
Tokyo Tamagawa University 3D Superresolution of Microscopic Images based on Variational Bayesian Inference via Chebyshev polynomials approximation
Yasuhiro Imoto, Shin-ichi Maeda, Shin Ishii (Kyoto Univ.) NC2013-111
Optical microscopes are used to elucidate changes in cellular functions mediated by morphological changes of cells in vi... [more] NC2013-111
pp.133-138
PRMU 2014-03-14
09:00
Tokyo   Hierarchical Single Image Super-Resolution Based on Dictionary Learning
Toshihiro Kitao, Osamu Hasegawa (Tokyo Inst. of Tech.) PRMU2013-192
Single image super-resolution, a technology to reconstruct a high-resolution image from a single low-resolution image, i... [more] PRMU2013-192
pp.145-150
ITS, IE, ITE-AIT, ITE-HI, ITE-ME [detail] 2013-02-19
11:00
Hokkaido Hokkaido Univ. Super-Resolution Specializing in Recognition of Road Assistance Signs
Kazuhiro Hirano, Gou Koutaki, Keiichi Uchimura, Daiki Hidaka (Kumamoto Univ.) ITS2012-48 IE2012-128
Among information which car navigation systems process, road signs are important for drivers to drive safely. The method... [more] ITS2012-48 IE2012-128
pp.281-285
NC, NLP 2013-01-24
11:10
Hokkaido Hokkaido University Centennial Memory Hall depth estimation from microscopic images using Bayesian inference
Yasuhiro Imoto, Shin-ichi Maeda, Shin Ishii (Kyoto Univ.) NLP2012-109 NC2012-99
In cellular biology, it is important to know 3D cellular shape to understand the cellular function. However, existing mi... [more] NLP2012-109 NC2012-99
pp.31-36
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