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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| HIP | 2022-10-18 10:50 |
Kyoto | Kyoto Terrsa (Primary: On-site, Secondary: Online) |
Examination of facial attractiveness features using geometric morphological analysis of and deep learning methods. Takanori Sano, Hideaki Kawabata (Keio Univ.)  HIP2022-52 |
In psychology, various studies have been conducted on the features that constitute facial attractiveness. In recent year... [more] | HIP2022-52 pp.26-31 |
| MI | 2022-09-15 10:00 |
Kanagawa | (Primary: On-site, Secondary: Online) |
Automatic Multi-Measure Classification of Hip Osteoarthritis Based on Digitally-Reconstructed Radiographs using Deep Learning Masachika Masuda, Mazen Soufi, Yoshito Otake (NAIST), Keisuke Uemura (Osaka Univ.), Masaki Takao (Ehime Univ.), Nobuhiko Sugano (Osaka Univ.), Yoshinobu Sato (NAIST) MI2022-49 |
Hip Osteoarthritis (HOA) is usually diagnosed by radiographs. In addition to the degree of cartilage degeneration, the d... [more] | MI2022-49 pp.1-4 |
| AP, SANE, SAT (Joint) |
2022-07-27 09:25 |
Hokkaido | Asahikawa Taisetsu Crystal Hall (Primary: On-site, Secondary: Online) |
[Invited Lecture]
A Study of Rain Attenuation Prediction Method by Deep Learning Yuji Komatsuya, Tetsuro Imai (TDU), Miyuki Hirose (Kyutech) AP2022-34 |
Recently, the frequency used in wireless systems has got higher significantly, such as B5G, HAPS, etc., and the importan... [more] | AP2022-34 pp.1-5 |
| EMD, WPT, EMCJ, PEM (Joint) |
2022-07-15 13:50 |
Tokyo | (Primary: On-site, Secondary: Online) |
Prediction of E-field Distribution in Indoor Environments Using Deep Learning Technique Liu Sen, Onishi Teruo, Taki Masao, Watanabe Soichi (NICT) EMCJ2022-34 |
As one of the important aspects of monitoring electromagnetic field (EMF) exposure levels, comprehensively grasping the ... [more] | EMCJ2022-34 pp.1-5 |
| CCS, NLP | 2022-06-09 17:15 |
Osaka | (Primary: On-site, Secondary: Online) |
Visualization of decisions from CNN models trained on OpenStreetMap images labeled based on traffic accident data Kaito Arase, Zhijian Wu, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) NLP2022-10 CCS2022-10 |
The authors have recently conducted training of Convolutional Neural Networks (CNNs) on OpenStreetMap images each of whi... [more] | NLP2022-10 CCS2022-10 pp.46-51 |
| RECONF | 2022-06-08 15:50 |
Ibaraki | CCS, Univ. of Tsukuba (Primary: On-site, Secondary: Online) |
Structural Sparsification of Activations and Weights for Low Latency Implementation of CNN Akira Jinguji, Naoto Soga, Hiroki Nakahara (Tokyo Tech) RECONF2022-22 |
(To be available after the conference date) [more] | RECONF2022-22 pp.95-100 |
| SeMI, IPSJ-DPS, IPSJ-MBL, IPSJ-ITS | 2022-05-26 10:03 |
Okinawa | (Primary: On-site, Secondary: Online) |
An Initial Study on Display-to-Camera Communication Systems Using Adversarial Attack on CNN Depth Estimation Model Lee Changseok, Hiraku Okada (Nagoya Univ.), Tadahiro Wada (Shizuoka Univ.), Chedlia Ben Naila, Masaaki Katayama (Nagoya Univ.) SeMI2022-2 |
Hidden screen-camera communication requires visual quality and robust communication performance. In this study, we demon... [more] | SeMI2022-2 pp.5-10 |
| SIP, BioX, IE, MI, ITE-IST, ITE-ME [detail] | 2022-05-19 10:00 |
Kumamoto | Kumamoto University Kurokami Campus (Primary: On-site, Secondary: Online) |
ECG waveform reconstruction method using FMCW radar sensing and transformer model Ren Anzai, Daiki Toda, Koichi Ichige (Yokohama National Univ.) SIP2022-4 BioX2022-4 IE2022-4 MI2022-4 |
In this paper, we propose a waveform reconstruction method for ECG (ElectroCardioGram) signals using a transformer, a ki... [more] | SIP2022-4 BioX2022-4 IE2022-4 MI2022-4 pp.19-24 |
| SIP, BioX, IE, MI, ITE-IST, ITE-ME [detail] | 2022-05-20 09:40 |
Kumamoto | Kumamoto University Kurokami Campus (Primary: On-site, Secondary: Online) |
User identification on Walking by Deep Learning Based on 3-axis Acceleration after Coordinate Transformation of Smartphone Pengfei Yang, Qun Yang, Yuji Watanabe (Nagoya City Univ.) SIP2022-17 BioX2022-17 IE2022-17 MI2022-17 |
In this paper, we first transform the 3-axis acceleration data of smart phone, which is left in our laboratory, from the... [more] | SIP2022-17 BioX2022-17 IE2022-17 MI2022-17 pp.85-90 |
| SIP, BioX, IE, MI, ITE-IST, ITE-ME [detail] | 2022-05-20 16:40 |
Kumamoto | Kumamoto University Kurokami Campus (Primary: On-site, Secondary: Online) |
3D Medical Image Segmentation Using 2.5D Deformable Convolutional CNN Yuya Okumura, Kudo Hiroyuki, Takizawa Hotaka (Tsukuba Univ.) SIP2022-29 BioX2022-29 IE2022-29 MI2022-29 |
An effective method to improve the accuracy of 3D medical image segmentation using deep learning is to use deformable co... [more] | SIP2022-29 BioX2022-29 IE2022-29 MI2022-29 pp.150-155 |
| SIP, BioX, IE, MI, ITE-IST, ITE-ME [detail] | 2022-05-20 17:00 |
Kumamoto | Kumamoto University Kurokami Campus (Primary: On-site, Secondary: Online) |
Deformable registration of 3D medical images with Deep Residual UNet Taiga Nakamura, Yuki Sato, Hiroyuki Kudo, Hotaka Takizawa (Univ. of Tsukuba) SIP2022-30 BioX2022-30 IE2022-30 MI2022-30 |
(To be available after the conference date) [more] | SIP2022-30 BioX2022-30 IE2022-30 MI2022-30 pp.156-160 |
| EA | 2022-05-13 16:25 |
Online | Online | Study on noise reduction with a single noisy speech based on Double-DIP Hien Oonaka (NITTC), Takuya Fujimura (Nagoya Univ.), Ryoichi Miyazaki (NITTC) EA2022-12 |
This paper proposes a new noise reduction method with an untrained Deep Neural Network ( DNN) for a single noisy speech.... [more] | EA2022-12 pp.54-61 |
| MSS, NLP | 2022-03-29 11:35 |
Online | Online | Decision of Acupoints in Acupuncture and Moxibustion Treatment by Deep Learning Hang Yang (Yamaguchi Univ.), Ren Wu (Yamaguchi Junior College), Mitsuru Nakata, Qi-Wei Ge (Yamaguchi Univ.) MSS2021-73 NLP2021-144 |
Most of the acupuncture and moxibustion treatments in Traditional Chinese Medicine are carried out based on the clinical... [more] | MSS2021-73 NLP2021-144 pp.95-100 |
| PRMU, IPSJ-CVIM | 2022-03-10 10:40 |
Online | Online | Medical Image Captioning with Information based on Medical Concepts Riku Tsuneda, Tetsuya Asakawa (TUT), Kazuki Shimizu, Takuyuki Komoda (THC), Masaki Aono (TUT) PRMU2021-64 |
Image Captioning for medical images is expected to augment the judgment of doctors and serve as a second opinion. Medica... [more] | PRMU2021-64 pp.25-30 |
| PRMU, IPSJ-CVIM | 2022-03-11 10:45 |
Online | Online | Self-supervised Contrastive Learning Using Triplet Loss for Offline Recognition of Handwritten Chinese Text lines Trung Tan Ngo, Hung Tuan Nguyen, Masaki Nakagawa (TUAT) PRMU2021-78 |
In this paper, we propose a framework for contrastive learning of visual representations using online triplet loss and a... [more] | PRMU2021-78 pp.115-120 |
| PRMU, IPSJ-CVIM | 2022-03-11 16:10 |
Online | Online | Spatial attention and parallel convolution for Real-time segmentation Yuki Sugimoto, Masaki Aono (TUT) PRMU2021-86 |
Semantic segmentation is an image recognition technique that classifies all objects and backgrounds by pixel in images. ... [more] | PRMU2021-86 pp.163-168 |
| CQ, IMQ, MVE, IE (Joint) [detail] |
2022-03-09 10:10 |
Online | Online (Zoom) | A study on player and ball tracking in tennis videos. Kosuke Matsumoto (Kobe univ.), Junki Tamae (iret), Nobutaka Kuroki (Kobe univ.), Kensuke Hirano (iret), Masahiro Numa (Kobe univ.) IMQ2021-16 IE2021-78 MVE2021-45 |
This paper proposes a player and ball tracking method in tennis videos with image processing techniques. The proposed me... [more] | IMQ2021-16 IE2021-78 MVE2021-45 pp.33-38 |
| CQ, IMQ, MVE, IE (Joint) [detail] |
2022-03-10 15:00 |
Online | Online (Zoom) | [Special Talk]
Lossless Image Coding using Inpainting-Oriented Deep Pixel Predictor Keita Takahashi (Nagoya Univ.) IMQ2021-31 CQ2021-122 IE2021-93 MVE2021-60 |
I will be presenting our previous paper that received IE special Award 2020 to encourage discussions for future directio... [more] | IMQ2021-31 CQ2021-122 IE2021-93 MVE2021-60 p.114(IMQ), p.124(CQ), p.114(IE), p.114(MVE) |
| IBISML | 2022-03-09 10:15 |
Online | Online | [Invited Talk]
--- Takahiro Tsukahara (Tokyo University of Science) IBISML2021-41 |
Turbulence of viscoelastic fluids, such as dilute polymer/surfactant solutions, is of practical importance, because it c... [more] | IBISML2021-41 p.34 |
| LOIS | 2022-03-03 13:00 |
Online | Online | Building a Grape Grain Detection Model for Table Grape Thinning Chisato Matsumoto, Ko Fujimura (Otsuma Women's Univ.) LOIS2021-40 |
This paper addresses the issue of counting grape berries from camera images to support the process of thinning grapes. I... [more] | LOIS2021-40 pp.1-6 |
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