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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 21 - 40 of 61 [Previous]  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] 2022-02-22
15:20
Online online A Note on Perceived Visual Content Estimation Based on Compressed Reconstruction Network Using Brain Signals While Gazing on Images
Takaaki Higashi, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama (Hokkaido University)
In this paper, we propose a method to reconstruct a perceived image using brain signals obtained during gazing images. S... [more] MMS2022-28 ME2022-53 AIT2022-28
pp.349-353
BCT, IEICE-CS, IPSJ-AVM, IEICE-IE [detail] 2021-11-25
10:50
Online Online Acceleration of Neural Network Visualization RISE by Reduction of Masks
Tomoki Nakada, Imamura Kousuke (Kanazawa Univ.)
Recently, various techniques have been proposed to visualize the basis for decisions in image recognition using neural n... [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
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
13:50
Online Online Detecting axillary lymph node metastasis of breast cancer with FDG-PET/CT images based on attention mechanism
Zongyao Li, Ren Togo, Kenji Hirata (Hokkaido Univ.), Kazuhiro Kitajima (Hyogo Med.), Junki Takenaka (Hokkaido Univ.), Yasuo Miyoshi (Hyogo Med.), Kohsuke Kudo, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.)
Determination of axillary nodal status is significant to treatment of breast cancer. Typically, the diagnosis of axillar... [more] MMS2021-7 ME2021-7 AIT2021-7
pp.33-36
IEICE-IE, IEICE-ITS, MMS, ME, AIT [detail] 2021-02-18
16:15
Online Online A Note on Cross-domain Recommendation Based on Multilayer Graph Analysis with Visual Features
Taisei Hirakawa, Keisuke Maeda, Takahiro Ogawa (Hokkaido Univ.), Satoshi Asamizu (NIT, Kushiro College), Miki Haseyama (Hokkaido Univ.)
In this paper, we improve the accuracy of cross-domain recommendation methods, which have been recently studied as a sol... [more] MMS2021-12 ME2021-12 AIT2021-12
pp.59-63
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]
3DMT, IEICE-SIS, IPSJ-AVM [detail] 2020-06-04
14:00
Online G Square (Hakodate Community Plaza) An experimental comparison of CNN- and CRNN-CTC for automatic phrase speech recognition systems using a children's speech database
Yunzhe Wang, Yu Tian (Hokkaido Univ.), Yoshikazu Miyanaga (CIST), Hiroshi Tsutsui (Hokkaido Univ.)
Children's speech recognition is still a challenging issue. In the case of children's speeches, the accuracy of conventi... [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]
HI, IEICE-IE, IEICE-ITS, MMS, ME, AIT [detail] 2020-02-27
16:35
Hokkaido Hokkaido Univ.
(Cancelled)
A Study on Region Segmentation of Color Laparoscopic Images after Contrast Enhancement Including Super-Resolution CNN by Image Regions
Norifumi Kawabata (Tokyo Univ. of Science), Toshiya Nakaguchi (Chiba Univ.)
As one of image pre-processing method to detect, recognize, and estimate lesion or characteristic region in medical imag... [more] MMS2020-22 HI2020-22 ME2020-50 AIT2020-22
pp.113-118
HI, IEICE-IE, IEICE-ITS, MMS, ME, AIT [detail] 2020-02-27
13:00
Hokkaido Hokkaido Univ.
(Cancelled)
Video Coding Using Optimal Intra Prediction Mode Estimation by CNN
Ryota Yokoyama, Masahiko Tahara (Waseda Univ.), Heming Sun (Waseda Univ./JST), Masaru Takeuchi (Waseda Univ.), Yasutaka Matsuo (NHK), Jiro Katto (Waseda Univ.)
These days, efficient video coding is required due to spread of video production and viewing, and high definition video.... [more]
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]
HI, IEICE-IE, IEICE-ITS, MMS, ME, AIT [detail] 2020-02-28
14:40
Hokkaido Hokkaido Univ.
(Cancelled)
Feature Interaction based Neural Network for Pair Matching Prediction
Luwei Zhang, Xueting Wang (UTokyo), Shintaro Kaneko, Yusuke Usui, Mizuki Kobayashi, Hiroki Kojima (eureka), Toshihiko Yamasaki (UTokyo)
Online dating services have become popular in modern society. Pair matching prediction between two users in these servic... [more]
HI, IEICE-IE, IEICE-ITS, MMS, ME, AIT [detail] 2020-02-28
15:25
Hokkaido Hokkaido Univ.
(Cancelled)
Make Your Presentation Better: Oral Presentation Support System using Linguistic and Acoustic Features
Shengzhou Yi (UTokyo), Takuya Yamamoto, Osamu Yamamoto, Yukiyoshi Katsumizu, Hiroshi Yumoto (P&I), Xueting Wang, Toshihiko Yamasaki (UTokyo)
In order to help presenters to improve their oral presentation skills, we propose a support system to provide impression... [more]
BCT, IEEE-BT 2020-02-20
14:15
Shiga   Learning-Based Channel Estimation for Massive MIMO with Pilot Contamination and Its Impact of Model Mismatch in Training
Hiroki Hirose, Tomoaki Ohtsuki (Keio Univ.)
In massive multiple-input multiple-output (MIMO), a base station (BS) needs accurate estimation of channel state informa... [more] BCT2020-24
pp.13-16
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
3DMT, IDY, IST [detail] 2019-12-20
14:55
Aichi NHK Nagoya Station Depth from Focal Stack by Deep Neural Network
Chen Baihui, Takahashi Keita, Fujii Toshiaki (Nagoya Univ.)
Light field theory is a heated topic in computer vision. Focal stack is one of the one of the most significant character... [more] IST2019-62 IDY2019-62 3DIT2019-37
pp.17-19
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
3DMT, HI 2019-03-08
14:40
Tokyo Kogakuin Univ. Tokyo Urban Tech Tower Campus Affective Voice Generator by using Generative Adversarial Networks
Takuya Asakura, Shunsuke Akama, Shoji Yamamoto (TMCIT)
A voice assistant device with internet connection has been spread in the world. An efficient use of this device is expec... [more] HI2019-58 3DIT2019-10
pp.37-40
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