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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 |
| NLP, MSS | 2023-03-17 10:40 |
Nagasaki | (Primary: On-site, Secondary: Online) |
Machine Learning-Based Risk Evaluation of Reconstruction Attack on Query System for Handling Privacy Data Mohd Anuaruddin Bin Ahmadon (山口大) MSS2022-96 NLP2022-141 |
In this paper, we proposed a method to evaluate the strength of a data privacy protection mechanism by separating the me... [more] | MSS2022-96 NLP2022-141 pp.160-163 |
| PRMU, IBISML, IPSJ-CVIM [detail] | 2023-03-02 09:40 |
Hokkaido | Future University Hakodate (Primary: On-site, Secondary: Online) |
Pruning for Producing Efficient DNNs: Neuron Selection and Reconstruction based on Final Layer Error Koji Kamma, Toshikazu Wada (Wakayama Univ.) PRMU2022-66 IBISML2022-73 |
Deep Neural Networks (DNNs) are dominant in the field of machine learning. However, because DNN models have large comput... [more] | PRMU2022-66 IBISML2022-73 pp.42-47 |
| 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 |
| PRMU | 2022-12-15 14:25 |
Toyama | Toyama International Conference Center (Primary: On-site, Secondary: Online) |
A DNN compression method based on output error of activation functions Koji Kamma, Toshikazu Wada (Wakayama Univ.) PRMU2022-38 |
Deep Neural Networks (DNNs) are dominant in the field of machine learning. However, because DNN models have large comput... [more] | PRMU2022-38 pp.34-39 |
| MBE, NC | 2022-12-03 13:30 |
Osaka | Osaka Electro-Communication University | A Proposal of the System to Extract Movement Onsets Depending on Individual Trials for Detail Analyses in the EEG Grasping-Type Discrimination Task Kosei Shibata, Phan Hoang Huu Duc, Hiroaki Wagatsuma (LSSE, Kyushu Institute of Technology) MBE2022-35 NC2022-57 |
In this study, we designed an extended data recording system to validate the onset timing to grab a target object in the... [more] | MBE2022-35 NC2022-57 pp.57-61 |
| 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 |
| MBE, NC (Joint) |
2022-03-02 16:10 |
Online | Online | XMCD-CT Reconstruction Using Compressed Sensing Tsukito Takizawa, Hayaru Shouno (The Univ. of Electro-Communications), Masaichiro Mizumaki (JASRI), Motohiro Suzuki (Kwansei Gakuin Univ.) NC2021-58 |
Observation of the magnetic domain structure is important for understanding the magnetic properties of materials includi... [more] | NC2021-58 pp.62-67 |
| EA, SIP, SP, IPSJ-SLP [detail] | 2022-03-02 13:25 |
Okinawa | (Primary: On-site, Secondary: Online) |
[Poster Presentation]
Sound Field Estimation from Small Number of Observations by Deep Learning with Difference-Approximation-Based Helmholtz-Equation Loss Function Kazuhide Shigemi, Shoichi Koyama, TomohikoNakamura, Hiroshi Saruwatari (UTokyo) EA2021-85 SIP2021-112 SP2021-70 |
We propose a single-frequency sound field estimation method from a small number of observations that uses a loss functio... [more] | EA2021-85 SIP2021-112 SP2021-70 pp.132-139 |
| EMM, EA, ASJ-H | 2021-11-15 13:30 |
Online | Online | [Poster Presentation]
Improving a tracking accuracy using Artificial Fiber Patterns by introducing Wrinkle on clothes and body shape determination Hiroki Urakawa, Kitahiro Kaneda, Keiichi Iwamura (TUS) EA2021-38 EMM2021-65 |
Due to the low cost of equipment, the number of surveillance cameras installed has increased significantly in recent yea... [more] | EA2021-38 EMM2021-65 pp.63-68 |
| MI | 2021-08-27 14:10 |
Online | Online | A Study of a Pose Estimation Method of Ultrasound Probe Using RNN Kanta Miura, Koichi Ito, Takafumi Aoki (Tohoku Univ.), Jun Ohmiya, Satoshi Kondo (KONICA MINOLTA) MI2021-22 |
In this paper, we propose an ultrasound (US) probe pose estimation method using deep learning for 3D US image reconstruc... [more] | MI2021-22 pp.2-7 |
| AP | 2021-06-17 15:30 |
Online | Online | [Invited Lecture]
Phase retrieval method and its applications Hiroyuki Arai (Yokohama National Univ.) AP2021-23 |
This reports presents the summary and application of Phase Retrieval (PR) method in which the phase information is recon... [more] | AP2021-23 pp.25-30 |
| IBISML | 2020-03-11 14:10 |
Kyoto | Kyoto University (Cancelled but technical report was issued) |
Accuracy of Brain Tumor Detection and Classification Based on Under Sampled k-Space Signals Tania Sultana, Sho Kurosaki, Yutaka Jitsumatsu, Junichi Takeuchi (Kyushu Univ.) IBISML2019-46 |
The prime concern of Magnetic Resonance Imaging (MRI) is to optimize examination time by assuring a good quality of the... [more] |
IBISML2019-46 pp.91-94 |
| SP, EA, SIP | 2020-03-02 13:00 |
Okinawa | Okinawa Industry Support Center (Cancelled but technical report was issued) |
[Poster Presentation]
Restoration of clipped signal using oversampling based on differentiable and convex loss function Natsuki Ueno, Shoichi Koyama, Hiroshi Saruwatari (Univ. Tokyo) EA2019-126 SIP2019-128 SP2019-75 |
A signal reconstruction method of clipped time-continuous signal using oversampling is proposed. The signal reconstructi... [more] | EA2019-126 SIP2019-128 SP2019-75 pp.147-152 |
| RISING (2nd) |
2019-11-26 10:30 |
Tokyo | Fukutake Learning Theater, Hongo Campus, Univ. Tokyo | [Poster Presentation]
Reconstruction of Occluded Human Skeleton Information Using Generative Adversarial Network Bochao Zhang, Takashi Nishitsuji, Takuya Asaka (Tokyo Metropolitan Univ.) |
Recently, the posture estimation technology using human skeleton data detected by deep learning has attracted attention.... [more] | |
| CCS, IN (Joint) |
2019-08-02 14:20 |
Hokkaido | KIKI SHIRETOKO NATURAL RESORT | Effect of shapes of activation functions on predictability in the echo state network Hanten Chang (Univ. of Tsukuba), Shinji Nakaoka (Hokkaido Univ.), Hiroyasu Ando (Univ. of Tsukuba) CCS2019-23 |
We investigate prediction accuracy for time series of Echo state networks with respect to several kinds of activation fu... [more] | CCS2019-23 pp.27-30 |
| ASN | 2019-01-29 14:25 |
Kagoshima | Kyuukamura Ibusuki | [Poster Presentation]
An Optimization of Drone Flight Plan based on Simulation for Precise Three-Dimensional Reconstruction Tatsuya Kobayashi, Zhang Heming, Shin Kawai, Hajime Nobuhara (Univ. Tsukuba) ASN2018-95 |
In the present three-dimensional reconstruction scheme using drone, various parameters such as the photographing positio... [more] | ASN2018-95 pp.89-93 |
| SRW | 2019-01-15 13:00 |
Kanagawa | Mitsubishi Electric (Oofuna) | 3D Point Cloud Data Simplification Method for Electromagnetic Simulation in Indoor Environment Zhihang Chen, Kentaro Saito (TokyoTech), Wataru Okamura, Yukiko Kishiki (KKE), Jun-ichi Takada (TokyoTech) SRW2018-49 |
Nowadays, using point clouds to do electromagnetic (EM) simulation has been attracting a lot of attention since point cl... [more] | SRW2018-49 pp.19-24 |
| IBISML | 2018-11-05 15:10 |
Hokkaido | Hokkaido Citizens Activites Center (Kaderu 2.7) | [Poster Presentation]
Posterior mean approximation solution combining multiple image prior distributions in MR image reconstruction Nanako Kubota, Ken Harada (Waseda Univ.), Koji Fujimoto, Tomohisa Okada (Kyoto Univ.), Masato Inoue (Waseda Univ.) IBISML2018-47 |
In the MR image reconstruction, combining multiple image prior distributions is preferred to obtain better results, but ... [more] | IBISML2018-47 pp.23-28 |
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