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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 21  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
AIT, 3DMT, OSJ-HODIC 2023-09-08
17:15
Tokyo Nihon Univ. College of Science and Technology (Surugadai Campus) Phase unwrapping is a technique used to recover the original phase from the wrapped phase in the range (−π, π]. Conventi... [more] AIT2023-147 3DMT2023-34
pp.33-36
ME, IEICE-EMM, IEICE-IE, IEICE-LOIS, IEE-CMN, IPSJ-AVM [detail] 2023-09-07
09:50
Osaka Osaka Metropolitan Univ.
(Primary: On-site, Secondary: Online)
Improving Performance of Convolutional Neural Network-Based Driver Behavior Recognition
Shengbiao Wang, Koji Iwano (Tokyo City Univ.)
This study investigates the automatic recognition of driver behaviors using images captured by in-vehicle cameras for th... [more] ME2023-90
pp.7-12
IST 2023-06-21
14:10
Tokyo Tokyo University of Science Morito Memorial Hall [Poster Presentation] Verification of the effectiveness of multitask learning for demosaicking and white-balancing
Yuki Nakagomi, Ryoya Takeuchi, Taishi Iriyama, Takashi Komuro (Saitama Univ)
In this study, we conducted an investigation on the learning effectiveness of jointly training demosaicking and white ba... [more] IST2023-25
pp.19-22
MMS, ME, AIT, IEICE-IE, IEICE-ITS [detail] 2023-02-22
14:00
Hokkaido Hokkaido Univ. Hierarchical Minimum-Sized Object Detection Method using Clustering Algorithm for UAV Autonomous Flight
Yusei Horikawa, Makoto Sugaya, Tetsuya Matsumura (Nihon Univ)
This paper describes an efficient minimum-sized object detection method in high-Resolution images for UAV autonomous fli... [more] MMS2023-31 ME2023-51 AIT2023-31
pp.235-238
IIEEJ, AIT 2022-10-30
16:00
Online on line A Trial of Recognition of Electronic Parts by Deep-Learning for Efficient Recycling
Yihong Tang, Tomonori Izumi (Ritsumeikan Univ.)
In order to improve material-recycling of disposed electronic appliances, we aim to develop a system to analyze and cate... [more] AIT2022-177
pp.19-22
3DMT 2022-10-17
15:40
Tochigi
(Primary: On-site, Secondary: Online)
Blurring correction using super-resolution on convolutional neural Network for aerial image with dihedral corner reflector array
Takumi Nagao, Daisuke Miyazaki (Osaka Metropolitan Univ.)
Aerial images with dihedral corner reflector array have the advantages that they do not have image aberration and restri... [more] 3DMT2022-47
pp.29-32
IEICE-SIP, IEICE-BioX, IEICE-IE, IEICE-MI, IST, ME [detail] 2022-05-20
16:40
Kumamoto Kumamoto University
(Primary: On-site, Secondary: Online)
3D Medical Image Segmentation Using 2.5D Deformable Convolutional CNN
Yuya Okumura, Kudo Hiroyuki, Takizawa Hotaka (Tsukuba Univ.)
An effective method to improve the accuracy of 3D medical image segmentation using deep learning is to use deformable co... [more]
IEICE-SIP, IEICE-BioX, IEICE-IE, IEICE-MI, IST, ME [detail] 2022-05-20
17:00
Kumamoto Kumamoto University
(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)
(To be available after the conference date) [more]
AIT, IIEEJ, AS, CG-ARTS 2022-03-08
10:30
Online Online Towards the 3D reconstruction from illustration images
Shen Qian, Itoh Takayuki (Ocha Univ.)
This paper presents our trial of 3D model reconstruction from illustration images. Recovery of the depth information i... [more] AIT2022-100
pp.243-245
ME 2022-02-12
10:45
Online online Study on Deep Learning Reconstruction of MRI Complex Images Using Real-value CNN
Itona Fukatsu, Kazuki Yamato, Satoshi Ito (Utsunomiya Univ.)
Application of compressed sensing has been applied to speed up the data acquisition time for MR imaging. In recent years... [more] ME2022-7
pp.25-27
AIT, IIEEJ, AS, CG-ARTS 2021-03-08
13:30
Online Online An Experimental Study on Recognizing Kuzushiji using Deep Learning
Fumiya Masuda, Syuhei Sato, Shangce Gao, Zheng Tang (Univ. of Toyama)
Kuzushiji is a typeface used in ancient documents, and has a characteristic of fluent handwriting with a brush. Ancient ... [more] AIT2021-90
pp.205-206
BCT, IEEE-BT 2022-02-17
13:20
Online TBD Channel Estimation to Mitigate Channel Aging in Massive MIMO with Pilot Contamination
Hiroki Hirose, Tomoaki Ohtsuki (Keio Univ.)
In a massive multiple-input mltiple-output (MIMO) system based on time division duplex (TDD), the channel state informat... [more] BCT2021-12
pp.13-16
IEICE-IE, IEICE-ITS, MMS, ME, 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)
As one of purpose of study on image segmentation, we are able to consider whether between object and background region c... [more]
IEICE-MI, IEICE-IE, IEICE-SIP, IEICE-BioX, IST, ME [detail] 2020-05-29
14:30
Online Online A method for analyze causes of deterioration of predict quality when Deep Learning is applied to instance segmentation
Tomonori Kubota, Takanori Nakao, Masafumi Katoh, Eiji Yoshida, Hidenobu Miyoshi (Fujitsu Lab.)
In this paper, we propose a method to analyze the cause of deterioration of prediction accuracy in instance segmentation... [more]
ME 2020-02-08
14:45
Kanagawa Kanto Gakuin University Convolutional Neural Network-based bird detection and species recognition from images automatically captured in real environment
Tiankuang Li, Hiroki Kuroda, Wataru Kitamura, Koji Iwano (Tokyo City Univ.)
Recently, "bird baths" have been installed in various places with the aim of conserving wild birds. In this research, we... [more] ME2020-26
pp.89-92
AIT, IIEEJ, AS, CG-ARTS 2019-03-12
15:45
Tokyo Waseda Univ. Semantic Segmentation for 3D Human Models
Satoshi Yamaguchi, Yoshihiro Kanamori, Jun Mitani (University of Tsukuba)
We propose a technique for semantic segmentation of 3D human models. Existing techniques for general 3D objects solely r... [more] AIT2019-80
pp.119-122
ME, IEICE-IE, IEICE-ITS, MMS, HI, AIT [detail] 2019-02-20
13:30
Hokkaido Hokkaido Univ. Evaluation of Multi-level Data Demodulation Using Convolutional Neural Networks for Holographic Data Storage
Yutaro Katano, Tetsuhiko Muroi, Nobuhiro Kinoshita, Norihiko Ishii (NHK)
Holographic data storage (HDS) is a promising next generation archival memory with large capacity, high data-transfer ra... [more] MMS2019-20 HI2019-20 ME2019-42 AIT2019-20
pp.205-208
ME, IEICE-IE, IEICE-ITS, MMS, HI, AIT [detail] 2019-02-20
13:15
Hokkaido Hokkaido Univ. A Note on Gastritis Detection from Gastric X-ray Images via Transfer Learning Approach
Misaki Kanai, Ren Togo, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.)
This paper presents a method for gastritis detection from gastric X-ray images via a transfer learning approach using a ... [more] MMS2019-37 HI2019-37 ME2019-59 AIT2019-37
pp.315-318
IEICE-ITS, IEICE-IE, MMS, HI, ME, AIT [detail] 2018-02-16
13:15
Hokkaido Hokkaido Univ. Suppression of Inter-symbol Interference by Convolutional Neural Networks for Holographic Data Storage
Yutaro Katano, Tetsuhiko Muroi, Kinoshita Nobuhiro, Norihiko Ishii (NHK)
Holographic data storage (HDS) is a promising for next generation archival media. In reproduction, reproduced data of tw... [more] MMS2018-25 HI2018-25 ME2018-25 AIT2018-25
pp.267-270
HI 2017-03-08
14:25
Tokyo Tokyo University of Agriculture and Technology A study on estimation of car orientation using convolution neural networks
Toyota Tomoya, Yasushi Tauchi, Yoshiki Mizukami (Yamaguchi Univ.)
While advanced driver assistance system becomes popular in these days, further improvement of detection and recognition ... [more] HI2017-57
pp.17-20
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