Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
IE, MVE, CQ, IMQ (Joint) [detail] |
2024-03-14 11:00 |
Okinawa |
Okinawa Sangyo Shien Center (Primary: On-site, Secondary: Online) |
[Invited Talk]
From Pixels to Precision: Passing into the Future of Super-Resolution Mastery Supatta Viriyavisuthisakul (PIM) IMQ2023-42 IE2023-97 MVE2023-71 |
Single Image Super-Resolution (SISR) involves reconstructing low-resolution images to enhance perceptual quality. Recent... [more] |
IMQ2023-42 IE2023-97 MVE2023-71 p.165 |
EMM, ITE-ME, IE, LOIS, IEE-CMN, IPSJ-AVM [detail] |
2023-09-07 16:30 |
Osaka |
Osaka Metropolitan University - Nakamozu Campus- (Hybrid) (Primary: On-site, Secondary: Online) |
Image Restoration using Super-Resolution and Deblur Akari Dakeno, Terumasa Aoki (TUT) LOIS2023-9 IE2023-19 EMM2023-56 |
With the development of deep learning, many studies on Super-Resolution (SR) using CNN have widely been done in the worl... [more] |
LOIS2023-9 IE2023-19 EMM2023-56 pp.12-17 |
IMQ |
2022-05-27 14:25 |
Tokyo |
|
Classification-ESRGAN
-- Synthesis of super-resolution images based on subject categorization -- Jingan Liu, Atsumu Harada, Naiwala P. Chandrasiri (Kogakuin Univ.) IMQ2022-3 |
In recent years, super-resolution techniques have been significantly developed based on deep learning. In particular, GA... [more] |
IMQ2022-3 pp.12-17 |
MI |
2022-01-26 13:00 |
Online |
Online |
Relationship between Image Quality and Learning Effect in Color Laparoscopic Images Generation by Generative Adversarial Networks Norifumi Kawabata (Hokkaido Univ.), Toshiya Nakaguchi (Chiba Univ.) MI2021-59 |
Improving of personal computer performance, it is possible for healthcare workers and related researchers to support for... [more] |
MI2021-59 pp.59-64 |
NLP |
2021-12-18 15:15 |
Oita |
J:COM Horuto Hall OITA |
On Weight Filter Generation Using an Attention Module in a Super-Resolution Method Keitaro Otani, Hidehiro Nakano (Tokyo City Univ.) NLP2021-66 |
In recent years, the development of computer technology has led to an increase in the number of systems that require lar... [more] |
NLP2021-66 pp.104-109 |
PRMU |
2021-12-16 11:00 |
Online |
Online |
Low-Resolution Iris Recognition with Image Super-Resolution for arbitrary magnification Tsubasa Bora (UEC), Takahiro Toizumi, Yuho Shoji, Yuka Ogino, Masato Tsukada (NEC), Masatsugu Ichino (UEC) PRMU2021-26 |
A low-resolution iris image reduces iris recognition accuracy. Some conventional researches tackle low-resolution iris r... [more] |
PRMU2021-26 pp.13-18 |
MI |
2021-03-17 11:00 |
Online |
Online |
Optimal Design and Quality Assessment of Color Laparoscopic Super-Resolution Image by Generative Adversarial Networks Norifumi Kawabata (Tokyo Univ. of Science), Toshiya Nakaguchi (Chiba Univ.) MI2020-91 |
The Generative Adversarial Networks (GAN) is unsupervised learning enabled to transform according to data characteristic... [more] |
MI2020-91 pp.186-190 |
MI |
2021-03-17 14:15 |
Online |
Online |
Super-resolution of thoracic CT volumes using high-frequency learning Ryosuke Kawai, Atsushi Saito (TUAT), Shoji Kido (Osaka Univ), Kunihiro Inai, Hirohiko Kimura (Fukui Univ), Akinobu Shimizu (TUAT) MI2020-97 |
We report the results of super-resolution using a new network model. Specifically, the reconstructed image is represente... [more] |
MI2020-97 pp.218-219 |
MBE, NC (Joint) |
2020-12-18 14:50 |
Online |
Online |
Super resolution for sea surface temperature with CNN and GAN Tomoki Izumi, Motoki Amagasaki, Kei Ishida, Masato Kiyama (Kumamoto Univ.) NC2020-28 |
In this paper, we use the deep neural networks (DNN)-based single image super-resolution (SISR) method for the super res... [more] |
NC2020-28 pp.1-6 |
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, CS, IPSJ-AVM, ITE-BCT [detail] |
2019-12-06 14:15 |
Iwate |
Aiina Center |
Image Restoration using a Codec Yoko Sogabe, Shiori Sugimoto, Takayuki Kurozumi, Hideaki Kimata (NTT) CS2019-86 IE2019-66 |
Image restoration, which is an inverse problem such as compressed
sensing and super-resolution, requires priors (e.g. ... [more] |
CS2019-86 IE2019-66 pp.105-109 |
EA, SIP, SP |
2019-03-14 13:30 |
Nagasaki |
i+Land nagasaki (Nagasaki-shi) |
[Poster Presentation]
Image Super-Resolution via Generative Adversarial Network Considering Objective Quality Hiroya Yamamoto, Daichi Kitahara, Akira Hirabayashi (Ritsumeikan Univ.) EA2018-115 SIP2018-121 SP2018-77 |
We propose a super-resolution method based on a conventional technique using the generative adversarial network (GAN). T... [more] |
EA2018-115 SIP2018-121 SP2018-77 pp.93-98 |
NC, MBE (Joint) |
2019-03-06 16:15 |
Tokyo |
University of Electro Communications |
Examination of Super Resolution and Noise Removal for MicroCT Image Miku Mashimo, Hayaru Shouno (UEC) NC2018-86 |
The purpose of this research is to increase the resolution of MicroCT (Computed Tomography) images.
The MicroCT image i... [more] |
NC2018-86 pp.227-232 |
IMQ, HIP |
2018-07-20 13:30 |
Hokkaido |
Sapporo City University, Satellite Campus |
[Invited Lecture]
Inpainting based on low-dimensional image approximation and its applications Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) IMQ2018-5 HIP2018-32 |
This paper introduces inpainting based on low-dimensional image approximation and its applications. Specifically, low-di... [more] |
IMQ2018-5 HIP2018-32 pp.1-4 |
IE |
2018-06-29 09:55 |
Okinawa |
|
Single Image Super-Resolution with Limited Number of Filters Yusuke Nakahara, Takuro Yamaguchi, Masaaki Ikehara (Keio Univ.) IE2018-22 |
In this paper, we propose a single image super-resolution with limited number of filters based on RAISR. RAISR is well k... [more] |
IE2018-22 pp.7-11 |
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 |
SIP, EA, SP, MI (Joint) [detail] |
2018-03-19 09:35 |
Okinawa |
|
Super-resolution of MRI images using SRCNN and its Evaluation Hikaru Niida, Kiminori Matsuzaki (Kochi Univ. of Tech.) MI2017-63 |
Super-resolution using deep convolutional neural networks (SRCNN) was proposed by Dong et al. in 2014. SRCNN has also be... [more] |
MI2017-63 pp.1-4 |
SIP |
2016-08-26 10:35 |
Chiba |
Chiba Institute of Technology, Tsudanuma Campus |
Super resolution of vein images using convolutional neural networks Koji Kashihara (Tokushima Univ.) SIP2016-80 |
If super-resolution techniques improve the quality of near-infrared images with a low signal-to-noise ratio, they could ... [more] |
SIP2016-80 pp.39-44 |
RECONF |
2016-05-19 13:00 |
Kanagawa |
FUJITSU LAB. |
FPGA Implementation of a Super-Resolution System Taito Manabe, Yuichiro Shibata, Kiyoshi Oguri (Nagasaki Univ.) RECONF2016-5 |
In this study, we implement a real-time super-resolution system for moving images using a convolutional neural network o... [more] |
RECONF2016-5 pp.17-22 |
IE, IMQ, MVE, CQ (Joint) [detail] |
2016-03-07 18:25 |
Okinawa |
|
Image Reduction Based on waifu2x Kohei Inoue, Kenji Hara, Kiichi Urahama (Kyushu Univ.) IMQ2015-52 IE2015-151 MVE2015-79 |
Recently, a high-quality image enlargement tool called waifu2x has been released and become the topic on the Internet. I... [more] |
IMQ2015-52 IE2015-151 MVE2015-79 pp.135-138 |