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All Technical Committee Conferences (Searched in: All Years)
| 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 |
| NC, MBE (Joint) |
2024-03-11 10:25 |
Tokyo | The Univ. of Tokyo (Primary: On-site, Secondary: Online) |
Potential of neural network for CT with divided cross sectional image using scattered X-ray Taiki Matsushita, Naohiro Toda (APU) MBE2023-68 |
In the X-ray CT(Computed Tomography) scattered X-rays have been removed by the detector grid. However several author hav... [more] | MBE2023-68 pp.1-4 |
| MI | 2024-03-03 09:41 |
Okinawa | OKINAWAKEN SEINENKAIKAN (Primary: On-site, Secondary: Online) |
A preliminary study on deep causal discovery model for image classification Ryohei Motoda, Megumi Nakao (Kyoto Univ.) MI2023-33 |
Although saliency map used in image classification can visualize the regions correlated with predicted class, it cannot ... [more] | MI2023-33 pp.11-14 |
| MI | 2024-03-04 09:36 |
Okinawa | OKINAWAKEN SEINENKAIKAN (Primary: On-site, Secondary: Online) |
[Short Paper]
Overfitting Prevention for PET Image Reconstruction using Early Stopping of Deep Image Prior based on Unbiased Risk Estimator Kaito Matsumura, Hidekata Hontani (NIT), Muneyuki Sakata (TMIG), Yuichi Kimura (KDU), Tatsuya Yokota (NIT) MI2023-65 |
In recent years, methods for PET image reconstruction using Deep Image Prior (DIP) have been actively studied. In PET im... [more] | MI2023-65 pp.106-108 |
| EMM | 2024-03-02 14:00 |
Overseas | Day1:JEJU TECHNOPARK, Day2:JEJU Business Agency | [Poster Presentation]
Classification of AI generated images by sparse coding Daishi Tanaka, Michiharu Niimi (KIT) EMM2023-89 |
In recent years, advancements in generative AI technologies have made it increasingly challenging for human vision to di... [more] | EMM2023-89 pp.1-6 |
| MI, MICT | 2023-11-14 13:00 |
Fukuoka | Brain Disease Classification Based on Brain MRI Images Using 3D-CNN Daisuke Hayashi, Akio Nagasaka, Yuji Mochizuki, Takayuki Hayashi (Hitachi), Takefumi Ueno (NHO Hizen Psychiatric Center) MICT2023-29 MI2023-22 |
Schizophrenia and Alzheimer’s disease are brain diseases that cause structural changes in the brain. In this paper, we c... [more] | MICT2023-29 MI2023-22 pp.15-20 |
|
| MI, MICT | 2023-11-14 15:40 |
Fukuoka | Improving image quality of sparse-view micro-CT using Wasserstein GAN Naoki Ikezawa, Takayuki Okamoto, Hideaki Haneishi (Chiba Univ.) MICT2023-36 MI2023-29 |
Applications of micro-CT in pathology and histology have been studied in recent years, and we need to shorten the scanni... [more] | MICT2023-36 MI2023-29 pp.45-47 |
|
| CQ, MIKA (Joint) |
2023-08-31 15:55 |
Fukushima | Tenjin-Misaki Sports Park | Semantic Communication with Masked Autoencoders: Enhancing Efficiency in Image Transmission Jiale Wu, Zhaoyang Du, Celimuge Wu, Tsutomu Yoshinaga (UEC) CQ2023-29 |
Semantic communication, a promising candidate for 6G technology, has become a research hot spot. However, existing studi... [more] | CQ2023-29 pp.20-25 |
| SANE | 2023-06-30 13:25 |
Kanagawa | JAXA Sagamihara Campus (Primary: On-site, Secondary: Online) |
Study on 3-D Bistatic Synthetic Aperture Radar Image Reconstruction Takuma Watanabe (Univ. of Toyama) SANE2023-19 |
Synthetic aperture radar (SAR) has been widely utilized in various research fields such as near-field radar cross sectio... [more] | SANE2023-19 pp.21-24 |
| SANE | 2023-05-23 11:00 |
Kanagawa | Information Technology R & D Center, MITSUBISHI Electric Corp. (Primary: On-site, Secondary: Online) |
Theoretical Study on Bistatic Circular SAR Image Reconstruction Takuma Watanabe (FSI) SANE2023-5 |
Circular synthetic aperture radar (CSAR) is a type of imaging radar in which the radar-carrying platform moves along a c... [more] | SANE2023-5 pp.24-29 |
| IMQ, IE, MVE, CQ (Joint) [detail] |
2023-03-17 14:05 |
Okinawa | Okinawaken Seinenkaikan (Naha-shi) (Primary: On-site, Secondary: Online) |
A Study on Image Inpainting Considering Local Appearance Consistency Tianxiang Zhang, Keisuke Doman, Yoshito Mekada (Chukyo Univ.) IMQ2022-77 IE2022-154 MVE2022-107 |
This paper proposes an image inpainting method which can preserve the local appearance consistency of reconstructed imag... [more] | IMQ2022-77 IE2022-154 MVE2022-107 pp.296-301 |
| MI | 2023-03-07 09:09 |
Okinawa | OKINAWA SEINENKAIKAN (Primary: On-site, Secondary: Online) |
Development of the imaging system for Scratch-PET: intraoperative PET with a hand-held probe-type detector Taiyo Ishikawa (Chiba Univ.), Yuma Iwao (QST/Chiba Univ.), Go Akamatsu, Sodai Takyu, Hideaki Tashima (QST), Takayuki Okamoto (Chiba Univ.), Taiga Yamaya (QST/Chiba Univ.), Hideaki Haneishi (Chiba Univ.) MI2022-104 |
We aimed at realizing a concept for the intraoperative PET imaging by scanning the surgical field with a hand-held detec... [more] | MI2022-104 pp.131-135 |
| MI | 2023-03-07 14:59 |
Okinawa | OKINAWA SEINENKAIKAN (Primary: On-site, Secondary: Online) |
Penalized 3D PET image reconstruction using deep image prior Fumio Hashimoto, Yuya Onishi, Kibo Ote (HPK), Hideaki Tashima, Taiga Yamaya (QST) MI2022-118 |
(To be available after the conference date) [more] | MI2022-118 pp.181-183 |
| SP, IPSJ-SLP, EA, SIP [detail] | 2023-02-28 10:40 |
Okinawa | (Primary: On-site, Secondary: Online) |
Image reconstruction with a diffusion model for robust image classification against unknown degradation Teruaki Akazawa (Tokyo Metro. Univ.), Yuma Kinoshita (Tokai Univ.), Hitoshi Kiya (Tokyo Metro. Univ.) EA2022-83 SIP2022-127 SP2022-47 |
This paper presents an image reconstruction method with a diffusion model for robust image classification against image ... [more] | EA2022-83 SIP2022-127 SP2022-47 pp.49-54 |
| IE | 2023-02-02 13:55 |
Tokyo | NII (Primary: On-site, Secondary: Online) |
Image reconstruction by warping shift-invariant systems in a holographic transparent screen camera Keiji Takahashi, Saori Takeyama, Masahiro Yamaguchi (Tokyo Tech) IE2022-52 |
A transparent screen camera, implemented using waveguide holographic optical elements, is combined with an image reconst... [more] | IE2022-52 pp.6-10 |
| CS, IE, IPSJ-AVM, ITE-BCT [detail] | 2022-11-25 11:30 |
Aichi | Nagoya Institute of Technology (Primary: On-site, Secondary: Online) |
Privacy-Preserving Facial Identification using Lensless Imaging Kohsuke Yamamura, Yoshihiro Maeda (TUS), Daisuke Sugimura (Tsuda Univ.), Takayuki Hamamoto (TUS) CS2022-59 IE2022-47 |
Lensless imaging is a method of obtaining optically encoded images without using a lens.In this imaging method, reconstr... [more] | CS2022-59 IE2022-47 pp.63-66 |
| PRMU | 2022-09-14 10:45 |
Kanagawa | (Primary: On-site, Secondary: Online) |
PRMU2022-13 |
In this paper, we propose an image correspondence method using machine learning and improve the accuracy of camera param... [more] | PRMU2022-13 pp.19-24 |
| AP, SANE, SAT (Joint) |
2022-07-29 09:25 |
Hokkaido | Asahikawa Taisetsu Crystal Hall (Primary: On-site, Secondary: Online) |
Radar Image Simulation Based on the Foldy-Lax Equations Including Multiple Scattering Effects Takuma Watanabe (FSI) SANE2022-31 |
Numerical models used in radar signal processing often assume a single or Born approximation, where the effects of multi... [more] | SANE2022-31 pp.49-54 |
| MI | 2022-07-08 17:00 |
Hokkaido | (Primary: On-site, Secondary: Online) |
[Short Paper]
Weakly-Supervised Focal Liver Lesion Detection in CT Images He Li, Yutaro Iwamoto (Ritsumeikan Univ.), Xianhua Han (Yamaguchi Univ.), Lanfen Lin, Ruofeng Tong, Hongjie Hu (Zhejiang Univ.), Akira Furukawa (Tokyo Metropolitan Univ.), Shuzo Kanasaki (Koseikai Takeda Hospital), Yen-Wei Chen (Ritsumeikan Univ.) MI2022-40 |
Convolutional neural networks have been widely used for anomaly detection and one of their most common methods is autoen... [more] | MI2022-40 pp.30-33 |
| SIP, BioX, IE, MI, ITE-IST, ITE-ME [detail] | 2022-05-20 16:20 |
Kumamoto | Kumamoto University Kurokami Campus (Primary: On-site, Secondary: Online) |
Visualization of Important Features for Classifier Decisions using Deep Image Synthesis Yushi Haku, Megumi Nakao, Tetsuya Matsuda (Kyoto Univ.) SIP2022-28 BioX2022-28 IE2022-28 MI2022-28 |
It is difficult to know the basis for the decisions of machine learning models, and it is necessary to provide a highly ... [more] | SIP2022-28 BioX2022-28 IE2022-28 MI2022-28 pp.144-149 |
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