| IEICE Technical Committee Submission System Conference Schedule |
Online Proceedings [Sign in] Tech. Rep. Archives |
All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| IE, ITS, ITE-MMS, ITE-ME, ITE-AIT [detail] | 2023-02-21 13:45 |
Hokkaido | Hokkaido Univ. | Automatic generation of eating order reports from first-person eating videos Kenshiro Sato, Yoko Yamakata, Kiyoharu Aizawa (UTokyo)  ITS2022-50 IE2022-67 |
By automatically generating meal reports used by dietitians for dietary guidance from video footage of meals recorded by... [more] | ITS2022-50 IE2022-67 pp.41-46 |
| IE, ITS, ITE-MMS, ITE-ME, ITE-AIT [detail] | 2023-02-22 09:30 |
Hokkaido | Hokkaido Univ. | Spurious Correlation with Dataset Imbalance in Image Recognition Hajime Oi, Toshihiko Yamasaki (UTokyo) ITS2022-58 IE2022-75 |
Though various methods against spurious correlation have been proposed, most of them conducted experiments under a limit... [more] | ITS2022-58 IE2022-75 pp.89-94 |
| ICTSSL, CAS | 2023-01-26 10:45 |
Tokyo | TBD (Primary: On-site, Secondary: Online) |
On a social game recommendation system using collaborative filtering with Julia Yoshiaki Shinjo, Ami Ukai, Hitoshi Miyamoto, Shun Nanai, Shunsuke Ohata, Takuto Ono, Tomoki Akiyama, Kotarou Naitou, Kazuya Ozawa, Hideaki Okazaki (SIT) CAS2022-64 ICTSSL2022-28 |
In this report, we consider and discuss how to build a social game recommendation system using collaborative filtering w... [more] | CAS2022-64 ICTSSL2022-28 pp.14-17 |
| PRMU | 2022-10-21 15:40 |
Tokyo | Miraikan - The National Museum of Emerging Science and Innovation (Primary: On-site, Secondary: Online) |
Action Recognition of Anime Ayako Sakuma, Naoshi Kaneko, Kazuhiko Sumi (Aoyama Gakuin Univ.) PRMU2022-28 |
This paper presents an action recognition method for anime characters. Since existing action recognition datasets focus... [more] |
PRMU2022-28 pp.35-40 |
| PRMU | 2022-09-15 10:15 |
Kanagawa | (Primary: On-site, Secondary: Online) |
Image retrieval for animated characters from original works, derivative works and merchandise Shiqi Mao (Ritsumeiken Univ), Longjiao Zhao (Nagoya Univ.), Yu Wang (Hitotsubashi Univ.), Jien Kato (Ritsumeiken Univ) PRMU2022-19 |
Recently, there are many successful models for retrieving animated characters. However, conventional studies have mainly... [more] | PRMU2022-19 pp.55-60 |
| SIS, IPSJ-AVM | 2022-06-10 13:00 |
Fukuoka | KIT(Wakamatsu Campus) (Primary: On-site, Secondary: Online) |
[Tutorial Lecture]
How to build a High-Precision and Efficient Robot Vision: Dataset Generation and Hardware Implementation for Deep Learning Hakaru Tamukoh (Kyutech) SIS2022-10 |
This tutorial lecture explains a construction method for high-precision and efficient robot vision that includes a semi-... [more] | SIS2022-10 pp.45-48 |
| PRMU, IPSJ-CVIM | 2022-03-11 14:15 |
Online | Online | Precise Affordance Annotation for Egocentric Action Video Datasets Zecheng Yu, Yifei Huang, Ryosuke Furuta, Yusuke Goutsu, Yoichi Sato (Univ. of Tokyo) PRMU2021-81 |
Object affordance has attracted a growing interest in computer vision. It is an important concept that builds a bridge b... [more] | PRMU2021-81 pp.133-138 |
| PRMU | 2021-12-16 10:30 |
Online | Online | Utilization of Synthetic Data for Mud Stain Removal from Single Image Shusaku Asada, Yoshihito Kokubo (Aisin Corp.), Masaru Koide (MACNICA, Inc.), Kohei Yamamoto (Corpy&Co., Inc.), Yoshihisa Suetsugu (Aisin Corp.) PRMU2021-24 |
Mud stains on the lens can cause serious damage to the various image recognition systems. Compared to raindrops, mud sta... [more] | PRMU2021-24 pp.1-6 |
| PRMU, IPSJ-CVIM | 2021-03-05 14:10 |
Online | Online | Improving Accuracy on Biased Datasets via Explanations of Deep Neural Networks Kazuki Adachi, Shin'ya Yamaguchi (NTT) PRMU2020-93 |
Although it is desirable that training datasets for deep learning have diverse features, datasets that have biased featu... [more] | PRMU2020-93 pp.139-144 |
| PRMU, IPSJ-CVIM | 2021-03-05 15:30 |
Online | Online | [Short Paper]
Accurate underwater model based dataset and analysis Shunsuke Takao (PARI) PRMU2020-96 |
Although underwater images are important in many fields, image degradation such as color distortion or declined contra... [more] |
PRMU2020-96 p.157 |
| PRMU | 2020-12-17 10:15 |
Online | Online | Synthesize talking anime-heads images by tunneling through human-heads domain Shun Fujiuchi, Ryo Hachiuma, Kunihiro Hasegawa, Hideo Saito (Keio Univ.) PRMU2020-39 |
Avatars are widely used on the Internet to establish non-verbal communication without exposing one's physical identity. ... [more] | PRMU2020-39 pp.7-11 |
| HCGSYMPO (2nd) |
2020-12-15 - 2020-12-17 |
Online | Online | Analysis of Relationship between Dishes and Foods towards Serving and Arrangement Support
-- Feature Analysis Focusing on Color Histogram -- Hayate Fukumoto, Mitsunori Matsushita, Ryosuke Yamanishi (Kansai Univ.) |
This paper investigate relationship between foods and plates based on each color histogram and its area. The goal of thi... [more] | |
| AI | 2020-12-10 13:30 |
Shizuoka | Online and HAMAMATSU ACT CITY (Primary: On-site, Secondary: Online) |
Study on Depth Estimation from 4D Light Field Videos Takahiro Kinoshita, Satoshi Ono (Kagoshima Univ.) AI2020-1 |
Depth (disparity) estimation from 4D Light Field (LF) images has been a research topic for the last couple of years. Mos... [more] | AI2020-1 pp.1-6 |
| SANE | 2020-11-25 10:20 |
Online | Online | Observation of Hokkaido-Iburi-Tobu Earthquake by Deep Learning of SAR Images Yang Yu, Josaphat Tetuko Sri Sumantyo (Chiba Univ.) SANE2020-27 |
Environment of Japan is situated by steep mountains and some disasters as typhoons, heavy rains and earthquakes that cau... [more] | SANE2020-27 pp.1-6 |
| PRMU | 2020-10-09 15:15 |
Online | Online | Trajectory Forecasting using Deep Learning: A Survey Horoaki Minoura, Tsubasa Hirakawa, Takayoshi Yamashita, Hironobu Fujiyoshi (Chubu Univ.) PRMU2020-29 |
Trajectory forecasting is the technology of predicting the path along which moving objects such as a pedestrian and vehi... [more] | PRMU2020-29 pp.62-78 |
| SIS | 2020-03-05 15:30 |
Saitama | Saitama Hall (Cancelled but technical report was issued) |
Deep Neural Networks for Object Detection and Classification on Domestic Service Robots Yutaro Ishida, Hakaru Tamukoh (Kyutech) SIS2019-45 |
We propose a semi-automatic data set generation method, and a system integration method of robot operating system (ROS) ... [more] | SIS2019-45 pp.45-50 |
| HWS, VLD [detail] | 2020-03-04 16:25 |
Okinawa | Okinawa Ken Seinen Kaikan (Cancelled but technical report was issued) |
Machine Learning Based Lithography Hotspot Detection Method and Evaluation Hidekazu Takahashi, Shimpei Sato, Atsushi Takahashi (Tokyo Tech) VLD2019-106 HWS2019-79 |
As VLSI device feature sizes are getting smaller and smaller, layout design has become more important to keep the yield... [more] |
VLD2019-106 HWS2019-79 pp.71-76 |
| SP, EA, SIP | 2020-03-03 09:00 |
Okinawa | Okinawa Industry Support Center (Cancelled but technical report was issued) |
Evaluation of vocal personality and expression for speech synthesized by non-parallel voice conversion with narrative speech Ryotaro Nagase, Keisuke Imoto, Ryosuke Yamanishi, Yoichi Yamashita (Ritsumeikan Univ.) EA2019-138 SIP2019-140 SP2019-87 |
In the technology of voice conversion, reproduction of emotion and intonation, pause is one of the research issues. Howe... [more] | EA2019-138 SIP2019-140 SP2019-87 pp.213-218 |
| ITE-HI, IE, ITS, ITE-MMS, ITE-ME, ITE-AIT [detail] | 2020-02-27 17:05 |
Hokkaido | Hokkaido Univ. (Cancelled but technical report was issued) |
A Note on Data Augmentation Method of 3D Pose Estimation for Illustration of Anime Character Nozomi Isami, Yuji Sakamoto (Hokkaido Univ.) |
Research on 3D pose estimation from photographs of real human using machine learning have already been proposed. However... [more] | |
| MI | 2020-01-29 10:05 |
Okinawa | OKINAWAKEN SEINENKAIKAN | A study of generalized generation of image features for computer-aided detection systems based on unsupervised learning with normal datasets
-- Experimental evaluations of feature generation by small datasets -- Kazuyuki Ushifusa, Mitsutaka Nemoto(, Yuichi Kimura, Takashi Nagaoka, Takahiro Yamada, Atsuko Tanaka (Kindai Uni.), Naoto Hayashi (The Uni of Tokyo Hosp) MI2019-68 |
In a computer-aided detection system, image features are essential factors. In this study, we propose an image feature g... [more] | MI2019-68 pp.15-18 |
[Return to Top Page]