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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
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Committee Date Time Place Paper Title / Authors Abstract Paper #
IEICE-SIP, IEICE-BioX, IEICE-IE, IEICE-MI, IST, ME [detail] 2022-05-19
16:10
Kumamoto Kumamoto University
(Primary: On-site, Secondary: Online)
[Invited Talk] Image and Video Restoration with Deep Learning
Satoshi Iizuka (Univ. of Tsukuba)
In this talk, I will introduce techniques for restoring black-and-white images and videos with high accuracy using deep ... [more]
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, ME, MMS, IEICE-IE, IEICE-ITS [detail] 2022-02-21
13:15
Online online Towards Universal Deep Image Compression
Koki Tsubota (UTokyo), Hiroaki Akutsu (Hitachi), Kiyoharu Aizawa (UTokyo)
In this paper, we investigate deep image compression towards universal usage. In image compression, it is desirable to b... [more]
AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] 2022-02-21
15:35
Online online Liver Tumor Segmentation by Using a Massive-Training Artificial Neural Network (MTANN) and its Analysis in Liver CT.
Yuqiao Yang, Muneyuki Sato, Ze Jin, Kenji Suzuki (Tokyo Tech)
Based on a 3D massive-training artificial neural network (MTANN) combined with a Hessian-based ellipse enhancer, a small... [more]
AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] 2022-02-22
14:40
Online online A Study on Object Detection in Omnidirectional Images Using Deep Learning
Yasuyuki Ishida, Toshio Ito (SIT)
A minimum sensor configuration is desired for a popular automatic vehicle. In this study, an omnidirectional camera with... [more]
BCT, IEICE-SIS 2021-10-08
10:00
Online online [Tutorial Lecture] The Past and The Future of Explainable AI Techniques
Yoshitaka Kameya (Meijo Univ.)
Machine learning models of high predictive performance, such as deep neural networks and ensemble models, now play a cen... [more]
BCT, IEEE-BT 2021-09-03
13:35
Online Online Convolutional Radio Modulation Recognition Networks with Attention Models in Wireless Systems
Haohui Jia, Na Chen, Minoru Okada (NAIST)
In modern wireless systems, deep learning (DL) shows promising performance for wireless signal processing. DL model driv... [more] BCT2021-35
pp.1-4
IEICE-IE, IEICE-ITS, MMS, ME, AIT [detail] 2021-02-18
14:50
Online Online A Note on Estimation of Deteriorated Regions Based on Anomaly Detection from Rubber Material Electron Microscope Images -- Verification of Feature Representations Extracted from Deep Learning Models --
Masanao Matsumoto, Ren Togo, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ)
This paper presents an anomaly detection method for estimation of deteriorated regions from rubber material electron mic... [more] MMS2021-9 ME2021-9 AIT2021-9
pp.43-46
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] 2020-05-28
15:40
Online Online People counting device using real-time face detection by AI camera
Koki Takebe, Junichi Akita (Kanazawa Univ)
Recent progress of semiconductor technology has been enabling small and inexpensive devices to execute the neural networ... [more] IST2020-31 ME2020-82
pp.37-40
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]
AIT, IIEEJ, AS, CG-ARTS 2020-03-13
15:30
Tokyo Tokyo University of Technology
(Cancelled)
Toward script translation in calligraphic works using deep learning -- Character recognition of seal scripts --
Shohei Ninomiya, Masanori Nakayama, Atsushi Miyazawa, Issei Fujishiro (Keio Univ.)
Calligraphic scripts are classified broadly into five types: seal, clerical, cursive, running, and standard. In this stu... [more] AIT2020-69
pp.75-78
AIT, IIEEJ, AS, CG-ARTS 2020-03-13
14:20
Tokyo Tokyo University of Technology
(Cancelled)
Speaker Identification for Evaluating Speaking Activities in Seminar using Deep Learning
Tomoki Akita, Norimasa Yoshida (Nihon Univ.)
In seminars, students are expected to participate actively. In this study, we would like to create a system that can me... [more] AIT2020-144
pp.313-314
HI, IEICE-IE, IEICE-ITS, MMS, ME, AIT [detail] 2020-02-27
14:00
Hokkaido Hokkaido Univ.
(Cancelled)
An Image Transformation Network for Privacy-Preserving Deep Neural Networks
Hiroki Ito, Yuma Kinoshita, Hitoshi Kiya (Tokyo Metro. Univ.)
We propose an image transformation network to generate visually-protected images for privacy-preserving deep neural netw... [more]
IEICE-SIS, IPSJ-AVM, 3DMT [detail] 2019-06-13
13:55
Nagasaki Fukue Culture Center Accuracy Improvement of Depth Estimation from a Single Still Image Using Feature Pyramid Network
Yudai Fukuda, Takuro Oki, Ryusuke Miyamoto (Meiji Univ.)
Depth estimation from a single shot image have become accurate drastically after emergence of deep
neural networks that... [more]

IST 2018-11-28
16:30
Tokyo Tamachi Campus, TITECH [Poster Presentation] Joint optimization for compressive video sensing and reconstruction under hardware constraints
Michitaka Yoshida (Kyushu Univ.), Akihiko Torii, Masatoshi Okutomi (Tokyo Tech), Kenta Endo, Yukinobu Sugiyama (Hamamatsu Photonics K. K.), RIn-ichiro Taniguchi (Kyushu Univ.), Hajime Nagahara (Osaka Univ.)
Compressive video sensing is the process of encoding multiple sub-frames into a single frame with controlled sensor expo... [more] IST2018-59
pp.1-2
IEICE-ITS, IEICE-IE, MMS, HI, ME, AIT [detail] 2018-02-15
15:45
Hokkaido Hokkaido Univ. A Note on Estimation of Users' Emotion Evoked During Listening to Music -- Performance Improvement Based on Deep Learning Method --
Hakusyou Dan, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.)
This paper presents a method that estimates users’ emotion evoked during listening to music. In our method, we use audio... [more] MMS2018-21 HI2018-21 ME2018-21 AIT2018-21
pp.201-206
IEICE-ITS, IEICE-IE, MMS, HI, ME, AIT [detail] 2018-02-16
13:00
Hokkaido Hokkaido Univ. Study of Multi-Scale Residual Network for Image-to-Image Translation
Rei Endo, Yoshihiko Kawai, Takahiro Mochizuki (NHK)
In recent years, deep neural networks have widely studied in various fields such as object recognition, scene classifica... [more] MMS2018-35 HI2018-35 ME2018-35 AIT2018-35
pp.319-322
ME, CE, IPSJ-AVM, IEICE-IE [detail] 2016-08-08
13:30
Fukuoka   Multi-stage identification of GGO candidate regions using DCNN and SVM
Kazuki Hirayama, Joo Kooi Tan, Hyoungseop Kim (KIT), Takatoshi Aoki (UOEH), Shoji Kido (YU)
Recently, the development of CAD (Computer Aided Diagnosis) system for the purpose of reducing the burden to the physici... [more]
 Results 1 - 20 of 20  /   
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