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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| BioX, SIP, IE, ITE-IST, ITE-ME [detail] | 2023-05-18 15:15 |
Mie | Sansui Hall, Mie University (Primary: On-site, Secondary: Online) |
 SIP2023-5 BioX2023-5 IE2023-5 |
Compressing video and images with lossy compression degrades input data.Therefore, image quality evaluation is necessary... [more] | SIP2023-5 BioX2023-5 IE2023-5 pp.16-21 |
| IMQ, IE, MVE, CQ (Joint) [detail] |
2023-03-15 13:15 |
Okinawa | Okinawaken Seinenkaikan (Naha-shi) (Primary: On-site, Secondary: Online) |
A Study on Quality Degradation Estimation Model for Transcoding Videos Ryo Saimi, Takanori Hayashi (Hiroshima Institute of Technology) CQ2022-86 |
To provide video delivery services with comfortable quality, it is important to design applications and networks based o... [more] | CQ2022-86 pp.37-42 |
| IMQ, IE, MVE, CQ (Joint) [detail] |
2023-03-16 15:40 |
Okinawa | Okinawaken Seinenkaikan (Naha-shi) (Primary: On-site, Secondary: Online) |
Iris Image Quality Assessment with Degradation Scores for Recognition Ryuichi Akashi, Yuho Shoji, Takahiro Toizumi, Atsushi Ito (NEC) IMQ2022-57 IE2022-134 MVE2022-87 |
In this paper, we propose an iris image quality assessment method to quantify the influence of each type of image degrad... [more] | IMQ2022-57 IE2022-134 MVE2022-87 pp.182-187 |
| IMQ | 2022-10-21 13:40 |
Aichi | E and S Building, Higashiyama Campus, Nagoya Univ. | HEVC Image Quality Assessment for eXtended Reality (XR) Based on 360 Degrees Camera Norifumi Kawabata (Computational Imaging Lab) IMQ2022-12 |
360 degrees video camera is often used in our life, event, information communication service, and Virtual Reality (VR), ... [more] | IMQ2022-12 pp.7-12 |
| SIS, ITE-BCT | 2022-10-14 09:40 |
Aomori | Hachinohe Institute of Technology (Primary: On-site, Secondary: Online) |
Creation of subjective evaluation datasets for Print Quality Assessment Ryosuke Tonegawa, Yosuke Sugiura, Nozomiko Yasui, Tetsuya Shimamura (Saitama Univ) SIS2022-15 |
There does not exist image quality assessment (IQA) dataset for image with print-specific defects so far. This dataset c... [more] | SIS2022-15 pp.21-26 |
| CCS, NLP | 2022-06-09 13:25 |
Osaka | (Primary: On-site, Secondary: Online) |
Learning Method for Image Denoising by Weighted Sum of Perceptual Quality Assessment Methods Takamichi Miyata (Chiba Inst. Tech.) NLP2022-2 CCS2022-2 |
Existing deep learning-based denoising methods employ mean squared error (MSE) as a loss function. As a result, the outp... [more] | NLP2022-2 CCS2022-2 pp.7-12 |
| SeMI, IPSJ-DPS, IPSJ-MBL, IPSJ-ITS | 2022-05-26 13:45 |
Okinawa | (Primary: On-site, Secondary: Online) |
Unsupervised Learning-based Non-invasive Fetal ECG Signal Quality Assessment Xintong Shi, Kohei Yamamoto, Tomoaki Ohtsuki (Keio Univ.), Yutaka Matsui, Kazunari Owada (Atom Medical Co., Ltd.) SeMI2022-4 |
For fetal heart rate (FHR) monitoring, the non-invasive fetal electrocardiogram (FECG) obtained from abdomen surface ele... [more] | SeMI2022-4 pp.15-19 |
| CQ, CS (Joint) |
2022-05-12 15:35 |
Fukui | Fukui (Fuku Pref.) (Primary: On-site, Secondary: Online) |
Study on a Subjective Quality Assessment Method for Multi-service Yuichiro Urata, Noritsugu Egi, Masataka Masuda (NTT) CQ2022-8 |
It is important for telecommunication carriers to monitor and manage quality of communication services they provide, and... [more] | CQ2022-8 pp.38-43 |
| EMM | 2022-03-07 15:40 |
Online | (Primary: Online, Secondary: On-site) (Primary: Online, Secondary: On-site) |
[Poster Presentation]
A Reversible Contrast Enhancement method in HSI Color Space Ayana Wakimizu (Chiba Univ.), Shoko Imaizimi (Chiba univ.) EMM2021-101 |
In this paper, we propose a new reversible image processing method for color images. While the conventional method enha... [more] |
EMM2021-101 pp.52-57 |
| IE, ITS, ITE-AIT, ITE-ME, ITE-MMS [detail] | 2022-02-21 12:45 |
Online | Online | Quality Assessment for 3D CG Image Colorization Using Visible Digital Watermarking after Noise Removal Based on Sparse Dictionary Learning Coding Norifumi Kawabata (Hokkaido Univ.) |
Thus far, we discussed to represent image data whether it is possible or not to represent meaning image how requirement ... [more] | |
| 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 |
| HCS | 2021-08-22 10:05 |
Online | Online | A Study on Performance Feedback and Bonus Payment in Crowdsourcing Services Yoshinori Hijikata (KGU) HCS2021-25 |
In recent years, crowdsourcing services have been used to diversify work styles of people and improve work efficiency in... [more] | HCS2021-25 pp.45-50 |
| CQ | 2021-08-04 15:30 |
Online | Online | A Factor Analysis of Uncomfortable Feeling caused by Image Retargeting in Retargeted Images using Subjective Assessment and Eye Measurement Yoshikazu Kawayoke (NIT, Ishikawa College), Yasuhiro Inazumi (Yamanashi Eiwa College) CQ2021-34 |
As the resolutions and aspect ratios of displays are becoming increasingly diverse, there is growing interest in image r... [more] | CQ2021-34 pp.64-69 |
| CS, CQ (Joint) |
2021-05-14 16:55 |
Online | On-line | Analysis on Stability of Subjective Quality Assessment for Video including quality change and stalling Noriko Yoshimura, Yuichiro Urata, Noritsugu Egi (NTT) CQ2021-20 |
In this study, assuming a 4K service, we conducted subjective quality evaluation experiments of videos with various qual... [more] | CQ2021-20 pp.86-91 |
| 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 |
| MBE, NC (Joint) |
2020-12-18 13:50 |
Online | Online | Highly Reliable Screening System for Infectious Diseases using Contact-less Medical Radar and Data Quality Assessment Machine Learning Koki Kumagai, Koichiro Ishibashi, Guanghao Sun (UEC) MBE2020-21 |
A quarantine based on body temperature has been carried out to prevent the spread of infectious diseases. However, body ... [more] | MBE2020-21 pp.8-11 |
| 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 |
| CQ, CS (Joint) |
2020-06-25 14:50 |
Online | Online | [Special Invited Talk]
Capture and Transparency in Perceptual Image Quality Assessment Damon M. Chandler (Shizuoka University) CS2020-6 CQ2020-10 |
Perceptual image and video quality assessment (QA) algorithms aim to estimate the quality of an image/video in a manner ... [more] | CS2020-6 CQ2020-10 p.23(CS), p.49(CQ) |
| CQ, CS (Joint) |
2020-06-26 11:00 |
Online | Online | QoE Evaluation of Cloud-based AR Application using HoloLens Hanayo Kajino, Kenji Kanai, Jiro Katto (Waseda Univ.) CS2020-10 |
Recently, thanks to the evolution of image processing technologies, practical application of Augmented Reality (AR), Vir... [more] | CS2020-10 pp.39-43 |
| IE, IMQ, MVE, CQ (Joint) [detail] |
2020-03-06 15:00 |
Fukuoka | Kyushu Institute of Technology (Cancelled but technical report was issued) |
A Study on Video Quality Design Considering User Attributes Tatsuya Nagata, Tomoki Mae, Takanori Hayashi (HIT) CQ2019-156 |
To provide video delivery services with comfortable quality, it is important to design applications and networks based o... [more] | CQ2019-156 pp.113-117 |
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