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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| IMQ | 2021-05-28 09:40 |
Online | Online | Self-supervised representation learning with grayscale images Yuichiro Sumi, Takuto Kojima (Nagoya Univ.), Kentaro Kutsukake (RIKEN), Tetsuya Matsumoto, Hiroaki Kudo (Nagoya Univ.), Yoshinori Takeuchi (Daido Univ.), Noritaka Usami (Nagoya Univ.)  IMQ2021-1 |
Multicrystalline silicon solar cells, which are most commonly used in residential photovoltaic systems, include regions ... [more] | IMQ2021-1 pp.1-4 |
| EMM, IT | 2021-05-21 14:25 |
Online | Online | A reversible data hiding method with high flexibility in compressive encrypted images Ryota Motomura, Shoko Imaizumi (Chiba Univ.), Hitoshi Kiya (Tokyo Metropolitan Univ.) IT2021-14 EMM2021-14 |
In this paper, we propose a reversible data hiding method in encrypted images, where both the com-pression efficiency an... [more] | IT2021-14 EMM2021-14 pp.78-83 |
| MI | 2021-05-17 15:10 |
Online | Online | [Short Paper]
Fundamental study of automatic segmentation of skeletal muscle regions on whole body CT images based on a 3D DeepCNN Kota Nozaki, Xiangong Zhou (Gifu Univ.), Naoki Kamiya (Aichi Prefectual Univ.), Takeshi Hara, Hiroshi Fujita (Gifu Univ.) MI2021-7 |
Amyotrophic lateral sclerosis (ALS) is an intractable disease in which voluntary muscles atrophy gradully due to degener... [more] | MI2021-7 pp.20-22 |
| MI | 2021-03-16 13:15 |
Online | Online | [Short Paper]
Feature extraction using AutoEncorder from nodular shadows on chest CT images Yuta Tanaka, Takeshi Hara, Xiangrong Zhou (Gifu Univ.), Masaki Matsusako, Taiki Nozaki (St. Luke's Hosp.) MI2020-71 |
Lung cancer mortality in men is 86.7% in 2018. If the benign and malignant lung cancer and the growth rate of nodules ca... [more] | MI2020-71 pp.99-101 |
| MI | 2021-03-17 10:45 |
Online | Online | [Short Paper]
Preliminary study for improving the performance of abdominal multi-phase CT image registration based on 3D deep CNN with a CycleGAN Ryotaro Fuwa, Xiangong Zhou, Takeshi Hara, Hiroshi Fujita (Gifu Univ.) MI2020-90 |
Deep learning is expected to be an approach to solve the problem of accurate medical image alignment. Recently, VoxelMor... [more] | MI2020-90 pp.182-185 |
| EMM | 2021-03-04 13:30 |
Online | Online | [Poster Presentation]
Object Boundary Correction for Monocular Depth Estimation Using Region Segmentation Ikuma Yasukawa, Shoko Imaizumi (Chiba Univ.) EMM2020-67 |
We propose a new method to generate high-quality depth images in this paper. The proposed method corrects object boundar... [more] | EMM2020-67 pp.1-6 |
| PRMU, IPSJ-CVIM | 2021-03-04 16:05 |
Online | Online | Media detection from cardiovascular OCT images based on deep learning jiwei zhang, kai wang (wakayama univ), Takashi Kubo (Wakayama Medical Univ), haiyuan wu (wakayama univ) PRMU2020-80 |
Medical image segmentation is an important issue in determining whether medical images can provide reliable evidence in ... [more] | PRMU2020-80 pp.65-70 |
| EA, US, SP, SIP, IPSJ-SLP [detail] | 2021-03-03 11:40 |
Online | Online | Estimation of Imagined Rhythm and Its Active Area from Electroencephalogram Using Deep Learning Naoki Yoshimura, Toshihisa Tanaka (TUAT) EA2020-63 SIP2020-94 SP2020-28 |
Rhythm is one element of music, and it is known that rhythm perception and imagery appear in an electroencephalogram (EE... [more] | EA2020-63 SIP2020-94 SP2020-28 pp.21-26 |
| OPE, OCS, OFT (Joint) [detail] |
2021-02-18 15:25 |
Online | Online | Infrared image transport using transversely disordered optical fibers of tellurite or chalcogenide glasses Asuka Nakatani, Tong Hoang Tuan, Shunei Kuroyanagi (TTI), Morio Matsumoto, Goichi Sakai Goichi (Furukawa Denshi), Takenobu Suzuki, Yasutake Ohishi (TTI) OFT2020-59 OPE2020-79 |
A transversely disordered optical fiber(TDOF) has been proposed in order to overcome the resolution limit of image trans... [more] | OFT2020-59 OPE2020-79 pp.17-20 |
| SeMI | 2021-01-20 14:50 |
Online | Online | SeMI2020-48 |
Although Convolutional Neural Network (CNN) showed high potential for automatic meter reading, it is facing various chal... [more] | SeMI2020-48 pp.27-32 |
| HIP | 2020-12-23 14:00 |
Online | Online | Analysis of human subjective evaluation using deep neural networks Yoshiyuki Sato (Tohoku Univ.), Kazuya Matsubara, Yuji Wada (Ritsmeikan Univ.), Satoshi Shioiri (Tohoku Univ.) HIP2020-68 |
In this research, we constructed an deep learning model to learn and predict several different subjective judgments by h... [more] | HIP2020-68 pp.77-80 |
| PRMU | 2020-12-18 15:25 |
Online | Online | Multi-Task Attention Learning for Fine-grained Recognition Dichao Liu (NU), Yu Wang (Rits), Kenji Mase (NU), Jien Kato (Rits) PRMU2020-63 |
Due to its inter-class similarity and intra-class variation, Fine-Grained Image Classification (FGIC) is an intrinsicall... [more] | PRMU2020-63 pp.145-150 |
| PRMU | 2020-12-18 17:00 |
Online | Online | An evaluation method of area detection AI based on contribution pattern variation with noise addition Yasuhide Mori, Naofumi Hama, Masashi Egi (Hitachi) PRMU2020-67 |
The processing of image recognition AI using machine learning is generally black-boxed, and grasping the operating chara... [more] | PRMU2020-67 pp.166-171 |
| SIS | 2020-12-01 14:50 |
Online | Online | A Study on Queue Area Detection Using Person Recognition and Tracking Ningyuan Li, Johei Matsuoka, Kazuya Tago (Tokyo Univ. of Tec.) SIS2020-33 |
The purpose of this study is to realize the measurement of the number of people in the queue by proposing a method for d... [more] | SIS2020-33 pp.31-34 |
| PRMU | 2020-10-09 10:45 |
Online | Online | Trial of three-dimensional extraction and classification of cell regions in the heart Asuma Takematsu, Masahiro Migita, Masashi Toda, Yuichiro Arima (Kumamoto Univ.) PRMU2020-21 |
Analysis of cardiomyocytes is urgently needed to elucidate the pathophysiology of heart disease. Cardiomyocytes are char... [more] | PRMU2020-21 pp.15-19 |
| SIS, ITE-BCT | 2020-10-01 10:30 |
Online | Online | A Proposal of Backlit Image Enhancement Method Improving Visibility of Dark Regions Masato Akai (Yamaguchi Univ.), Yoshiaki Ueda (Fukuoka Univ.), Takanori Koga (Kindai Univ.), Noriaki Suetake (Yamaguchi Univ.) SIS2020-11 |
A backlit image often includes both of bright regions and extremely dark regions. The visibility of the dark regions in ... [more] | SIS2020-11 pp.5-10 |
| MI | 2020-09-03 10:00 |
Online | Online | Lung region segmentation of thoracoscopic image with unsupervised image translation Jumpei Nitta, Megumi Nakao (Kyoto Univ.), Keiho Imanishi (e-Growth Co. Ltd.), Tetsuya Matsuda (Kyoto Univ.) MI2020-19 |
In endoscopic surgery, it is necessary to understand the three-dimensional structure of the target region to improve saf... [more] | MI2020-19 pp.13-18 |
| MI | 2020-09-03 11:00 |
Online | Online | [Short Paper]
Quantitative analysis of epicardial adipose tissue by two-stage segmentation network and its system development Takayuiki Nagata, Yutaro Iwamoto, Zhao Ziyu (Ritsumeikan Univ), Yuji Tezuka, Hiroki Okada, Kiyosumi Maeda, Atsuyuki Wada, Atsunori Kashiwagi (Kusatsu General Hospital), Yen-Wei Chen (Ritsumeikan Univ) MI2020-23 |
Diabetes is thought to lead to vascular disease and arteriosclerosis, and there is a need for early detection and treatm... [more] | MI2020-23 pp.27-30 |
| IMQ, HIP | 2020-08-21 14:30 |
Online | Online | Development and accuracy verification of a simple bus passenger counting system using image processing Shina Takano, Takeshi Natsuno, Yuukou Horita (Univ. of Toyama) IMQ2020-1 HIP2020-21 |
In rural areas, although the environment surrounding public transportation is harsh, residents need regional public tran... [more] | IMQ2020-1 HIP2020-21 pp.1-4 |
| MI, IE, SIP, BioX, ITE-IST, ITE-ME [detail] | 2020-05-29 15:10 |
Online | Online | Distant pedestrian detection from nighttime NIR video by moving-region zooming Atsuki Hiramatsu, Yusuke Kameda (TUS), Hiroshi Ikeoka (Fukuyama Univ.), Takayuki Hamamoto (TUS) SIP2020-16 BioX2020-16 IE2020-16 MI2020-16 |
Highly accurate pedestrian detection technology is required for functions such as automatic emergency braking, which are... [more] | SIP2020-16 BioX2020-16 IE2020-16 MI2020-16 pp.79-83 |
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