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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| CQ, CBE (Joint) |
2022-01-27 16:05 |
Ishikawa | Kanazawa（Ishikawa Pref.） (Primary: On-site, Secondary: Online) |
Proposal and evaluation of 3D-point object estimation method based on probability space representation Hiroaki Sato, Shin'ichi Arakawa, Masayuki Murata (Osaka Univ.)  CQ2021-83 |
New network services are expected to emerge using real spatial information in remote areas. For the advancement of servi... [more] | CQ2021-83 pp.39-44 |
| NS, NWS (Joint) |
2022-01-28 13:05 |
Online | Online | A Case for Federated Learning with Training Data Generation for Walking Navigation Yuto Hoshino, Hiroki Matsutani (Keio Univ.) NS2021-119 |
(To be available after the conference date) [more] | NS2021-119 pp.50-55 |
| MI, MICT [detail] | 2021-11-05 10:45 |
Online | Online | [Short Paper]
A Method for Extracting and Visualizing Calcified Areas from Coronary OCT Images. Ryo Oikawa, Toru Kato, Akio Doi (Iwate Prefectural Univ.), Masaru Ishida (Iwate Medical Univ.) MICT2021-32 MI2021-30 |
Optical coherence tomography (OCT) has been widely used to diagnose calcified areas in coronary arteries in the last dec... [more] | MICT2021-32 MI2021-30 pp.22-25 |
| MBE, NC (Joint) |
2021-10-28 15:05 |
Online | Online | Enhancement of spatio-temporal coding performance in spiking neural network and its application to hazard detection for landing of spacecrafts Hideaki Kinoshita, Shinichi Kimura (TUS), Seisuke Fukuda (JAXA) NC2021-21 |
Spiking neural networks (SNNs) are a neuromimetic computational architecture that has attracted much attention in recent... [more] | NC2021-21 pp.16-21 |
| MI | 2021-07-08 14:30 |
Online | Online | Extraction of Calcified Regions from OCT Images Using Deep Learning Ryo Oikawa, Toru Kato, Akio Doi, Basabi Chakraborty (Iwate Prefectural Univ.), Masaru Ishida (Iwate Medical Univ.) MI2021-12 |
Stenosis or occlusion of coronary arteries leads to angina attacks and myocardial infarctions, and coronary artery disea... [more] | MI2021-12 pp.15-19 |
| SIS | 2021-03-04 13:30 |
Online | Online | Improvement of Detection Accuracy of Calcification Regions from Dental Panoramic Radiograph Using Deep Learning Taito Murano, Mitsuji Muneyasu, Soh Yoshida, Akira Asano (Kansai Univ.), Keiichi Uchida (Matsumoto Dental Univ. Hospital), Dewake Nanae, Yasuaki Ishioka, Nobuo Yoshinari (Matsumoto Dental Univ.) SIS2020-45 |
Dental panoramic radiographs may show calcified areas that are a sign of vascular disease. Finding these areas in dentis... [more] | SIS2020-45 pp.55-60 |
| PRMU, IPSJ-CVIM | 2021-03-05 14:10 |
Online | Online | A Consideration on Suspicious Object Detection by Mixup and Improved U-Net Naruki Kanno, Wataru Kameyama, Toshio Sato, Yutaka Katsuyama, Takuro Sato (Waseda Univ.) PRMU2020-90 |
In this paper, on suspicious object detection by using semantic segmentation, we study the effectiveness of Mixup data a... [more] | PRMU2020-90 pp.121-126 |
| PRMU, IPSJ-CVIM | 2021-03-05 14:25 |
Online | Online | Semantic Segmentation based on MobileNet Extended with FPN Yuki Sugimoto, Masaki Aono (TUT) PRMU2020-91 |
Semantic Segmentation is attracting attention in autonomous driving, but high-precision models require a huge amount of ... [more] | PRMU2020-91 pp.127-132 |
| IE, ITS, ITE-MMS, ITE-ME, ITE-AIT [detail] | 2021-02-18 14:50 |
Online | Online | Production and Evaluation of Data Set for Semantic Segmentation of 3D CG Image by H.265/HEVC Norifumi Kawabata (Tokyo Univ. of Science) ITS2020-30 IE2020-44 |
As one of purpose of study on image segmentation, we are able to consider whether between object and background region c... [more] | ITS2020-30 IE2020-44 pp.19-24 |
| CPSY, RECONF, VLD, IPSJ-ARC, IPSJ-SLDM [detail] | 2021-01-26 09:50 |
Online | Online | FPGA Implementation of Semantic Segmentation on LWIR Images for Autonomous Robot Yuichiro Niwa (ATLA), Taiki Fujii (eSOL) VLD2020-57 CPSY2020-40 RECONF2020-76 |
Recently, deep learning of images has made remarkable progress, and its results are being applied to the automatic reco... [more] |
VLD2020-57 CPSY2020-40 RECONF2020-76 pp.101-106 |
| PRMU | 2020-12-17 14:55 |
Online | Online | Improving the accuracy of unsupervised segmentation by introducing a Laplacian filter loss function
-- Application to automotive wire harness components -- Yuki Matsumoto (SEI) PRMU2020-45 |
Semantic segmentation, in which images are classified into pixel-by-pixel classes by deep learning, has been widely stud... [more] | PRMU2020-45 pp.42-46 |
| IE, IMQ, MVE, CQ (Joint) [detail] |
2020-03-06 13:25 |
Fukuoka | Kyushu Institute of Technology (Cancelled but technical report was issued) |
Detection of running area from forest road images with different image quality using deep learning Misato Ushiro, Tetsuya Higashino, Yuukou Horita (Univ. of Toyama) IMQ2019-60 IE2019-142 MVE2019-81 |
Natural disasters such as falling rocks and landslides are increasing year by year on forest roads in hilly and mountain... [more] | IMQ2019-60 IE2019-142 MVE2019-81 pp.231-234 |
| ITE-HI, IE, ITS, ITE-MMS, ITE-ME, ITE-AIT [detail] | 2020-02-27 10:00 |
Hokkaido | Hokkaido Univ. (Cancelled but technical report was issued) |
A lane estimation method by road image analysis with influence reduction of other vehicles Kohei Mori, Yuki Yokohata, Takahiro Hata, Aki Hayashi, Kazuaki Obana (NTT) ITS2019-31 IE2019-69 |
We have been promoting smart mobility like advanced navigation services or driving support services. GPS is one of usefu... [more] | ITS2019-31 IE2019-69 pp.135-138 |
| IPSJ-SLDM, RECONF, VLD, CPSY, IPSJ-ARC [detail] | 2020-01-22 16:55 |
Kanagawa | Raiosha, Hiyoshi Campus, Keio University | A Comparison of Filter for Convolutional Neural Network towards Hardware Implementation Kosuke Akimoto, Youki Sada, Shimpei Sato, Hiroki Hakahara (Tokyo Tech) VLD2019-64 CPSY2019-62 RECONF2019-54 |
Convolutional neural networks have high recognition accuracy in computer vision task, and many of the learned filters ar... [more] | VLD2019-64 CPSY2019-62 RECONF2019-54 pp.61-66 |
| HCGSYMPO (2nd) |
2019-12-11 - 2019-12-13 |
Hiroshima | Hiroshima-ken Joho Plaza (Hiroshima) | Class Augmentation For Semantic Segmentation by Integrating Multiple Methods Qiusheng Wang, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase (Nagoya Univ.) |
Along with the development of autonomous driving and Augmented Reality (AR), we need technologies that can help understa... [more] | |
| ITE-BCT, SIS | 2019-10-24 11:50 |
Fukui | Fukui International Activities Plaza | A Study on Intersection Detection and Recognition Using Only a Monocular Camera for Visual Navigation Kouchi Matsutani, Takuto Watanabe, Takuro Oki, Ryusuke Miyamoto (Meiji Univ.) SIS2019-12 |
To realize autonomous mobile robot system that does not require expensive sensing devices such as LiDAR and RADAR, we th... [more] | SIS2019-12 pp.5-10 |
| MVE | 2019-10-10 14:50 |
Hokkaido | Segnet and U-Net Implementations for Water Hyacinth Semantic Segmentation in Thailand Supatta Viriyavisuthisakul, Parinya Sanguansat (PIM), Toshihiko Yamasaki (UTokyo) MVE2019-25 |
Water Hyacinth is an aquatic weed that can spread very quickly. Normally, it can be found in a dam or river. Water Hyaci... [more] | MVE2019-25 pp.9-12 |
|
| IE, EMM, LOIS, IEE-CMN, ITE-ME, IPSJ-AVM [detail] | 2019-09-19 15:35 |
Niigata | Tokimeito, Niigata University | Digital watermarking method against print-cam attack using deep learning for synchronization Hiroyuki Imagawa, Motoi Iwata, Koichi Kise (Osaka Pref. Univ.) LOIS2019-12 IE2019-25 EMM2019-69 |
In this paper, we propose a novel watermarking method against print-cam attack. Digital watermarking is used to get inf... [more] |
LOIS2019-12 IE2019-25 EMM2019-69 pp.31-36 |
| RECONF | 2019-05-10 10:00 |
Tokyo | Tokyo Tech Front | An FPGA Implementation of the Semantic Segmentation Model with Multi-path Structure Youki Sada, Masayuki Shimoda, Shimpei Sato, Hiroki Nakahara (titech) RECONF2019-10 |
Since the convolutional neural network has a high-performance recognition accuracy, it is expected to implement variou... [more] |
RECONF2019-10 pp.49-54 |
| MI | 2019-01-22 13:20 |
Okinawa | Cell image segmentation by Attention module Yuki Hiramatsu, Kazuhiro Hotta (Meijo Univ.) MI2018-79 |
(To be available after the conference date) [more] | MI2018-79 pp.77-80 |
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