Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
SIP |
2024-03-21 14:25 |
Ibaraki |
Center for Computational Sciences, University of Tsukuba |
Bunch of Tricks for Improving Shuttlecock Detection from Badminton Videos Muhammad Abdul Haq (TMU), Shuhei Tarashima (NTT Com), Norio Tagawa (TMU) |
Accurate identification of the shuttlecock is necessary for video analysis in badminton matches, but, it remains difficu... [more] |
SIP2024-4 pp.8-11 |
AIT, IIEEJ, AS, CG-ARTS |
2024-03-05 14:30 |
Tokyo |
Tokyo University of Technology |
Card game AI applying reinforcement learning with Unity ML-Agents Tatsuya Watanabe, Junichi Yamamoto (THCU) |
In recent years, there has been active research in game AI, with AI agents reaching the level of professional players in... [more] |
AIT2024-138 pp.375-376 |
IEICE-ITS, IEICE-IE, ME, AIT, MMS [detail] |
2024-02-20 14:00 |
Hokkaido |
Hokkaido Univ. |
A Study of Action Classification Methods from Videos Using Unsupervised Learning Ayana Rikimaru (NIT(KOSEN), NC) |
The purpose of this study is to develop a system for automatic surveillance, and to examine whether human behavior in vi... [more] |
MMS2024-30 ME2024-46 AIT2024-30 pp.148-151 |
BCT, IEEE-BT |
2024-02-16 10:50 |
Aichi |
Nagoya International Center (Primary: On-site, Secondary: Online) |
Adapter-Based Fine-Tuning for Multi-Task Learning Based CSI Feedback in FDD Massive MIMO Systems Mayuko Inoue, Tomoaki Ohtsuki (Keio Univ) |
A multi-task learning-based Channel State Information (CSI) feedback has been proposed to obtain the CSI of the downlink... [more] |
BCT2024-27 pp.25-28 |
3DMT |
2023-10-02 13:05 |
Aichi |
(Primary: On-site, Secondary: Online) |
[Tutorial Invited Lecture]
From Mathematical Modeling to Data-Driven Optimization
-- Compressive Light Field Acquisition Undergoes Paradigm Shift -- Keita Takahashi (Nagoya Univ.) |
The light field is a basic representation for 3-D visual information, and it is usually treated as a set of images taken... [more] |
3DMT2023-35 p.1 |
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 |
IIEEJ, AIT |
2023-06-04 11:00 |
Tokyo |
TOKYO CITY UNIVERSITY (Primary: On-site, Secondary: Online) |
A study of feature extraction methods for clusters in image classification using deep metric learning
-- Visualization of features using factor information common to clusters -- Haruya Tanaka, Chanjin Seo, Jun Ohya (Waseda Univ.), Hiroyuki Ogata (Seikei Univ.) |
In recent years, the running population has been increasing, and demand for coaching systems for amateur runners is expe... [more] |
AIT2023-138 pp.55-58 |
AIT, IIEEJ, AS, CG-ARTS |
2023-03-06 12:40 |
Tokyo |
Tokyo Polytechnic Univ. (Nakano) (Primary: On-site, Secondary: Online) |
Semiautomatic generation of vignette illustrations from video
-- Reflecting viewer preferences -- Mayu Namai, Issei Fujishiro (Keio Univ.) |
A variety of summarization techniques have recently been published to manage the growing volume of media data, but most ... [more] |
AIT2023-120 pp.301-304 |
MMS, ME, AIT, IEICE-IE, IEICE-ITS [detail] |
2023-02-21 11:00 |
Hokkaido |
Hokkaido Univ. |
A note on text prompt tuning in cross-modal image retrieval for a specific database Huaying Zhang, Rintaro Yanagi, Ren Togo, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
With the development of storage devices and the Internet, the number of users creating personal image databases has incr... [more] |
MMS2023-3 ME2023-23 AIT2023-3 pp.11-15 |
MMS, ME, AIT, IEICE-IE, IEICE-ITS [detail] |
2023-02-21 14:45 |
Hokkaido |
Hokkaido Univ. |
A Note on Improvement of Binauralization Performance Based on Multi-view Learning on 360° Videos Masaki Yoshida, Ren Togo, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
In this paper, we propose a binaural audio generation method based on multi-view learning using 360◦ videos. Conventiona... [more] |
MMS2023-13 ME2023-33 AIT2023-13 pp.65-69 |
MMS, ME, AIT, IEICE-IE, IEICE-ITS [detail] |
2023-02-21 15:30 |
Hokkaido |
Hokkaido Univ. |
Evaluating The Effectiveness of Data Augmentation for Learning TrackNetV2 Yushan Wang (TMU), Shuhei Tarashima (NTT Com), Norio Tagawa (TMU) |
Data augmentation has been widely used in a variety of deep learning tasks, mostly with a positive impact on the results... [more] |
MMS2023-16 ME2023-36 AIT2023-16 pp.81-84 |
MMS, ME, AIT, IEICE-IE, IEICE-ITS [detail] |
2023-02-21 15:45 |
Hokkaido |
Hokkaido Univ. |
A Residual U-Net Architecture for Shuttlecock Detection Muhammad Abdul Haq (TMU), Shuhei Tarashima (NTT Com), Norio Tagawa (TMU) |
Detection of fast-moving shuttlecocks is essential for badminton video analysis. Several methods based on deep learning ... [more] |
MMS2023-17 ME2023-37 AIT2023-17 pp.85-88 |
MMS, ME, AIT, IEICE-IE, IEICE-ITS [detail] |
2023-02-21 10:30 |
Hokkaido |
Hokkaido Univ. |
Improving Fashion Compatibility Prediction with Color Distortion Prediction Ling Xiao, Toshihiko Yamasaki (UTokyo) |
Fashion compatibility prediction is suffering from the fact that the labeled dataset may become outdated quickly due to ... [more] |
|
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 |
BCT, IEEE-BT |
2023-02-16 14:30 |
Osaka |
Osaka Museum of History |
Predicting Temperature Rise Using Machine Learning in Microwave Heating Tohgo Hosoda, Aditya Rakhmadi, Kazuyuki Saito (Chiba Univ.) |
In recent years, research on machine learning has been active, and use of technology been increasing in various fields w... [more] |
BCT2023-18 pp.1-4 |
ME, SIP, TOKAI |
2022-12-07 10:50 |
Aichi |
(Primary: On-site, Secondary: Online) |
[Short Paper]
3D Facial Recognition for Genetic Studies based on PointNet++ Kazuma Okada, Takuma Terada, Jiaqing Liu (Ritsumeikan Univ.), Tomoko Tateyama (Fujita Health University), Ryosuke Kimura (Ryukyu Univ.), Yen Wei Chen (Ritsumeikan Univ.) |
Recently, the development of genetic research has found a relationship between human face shape and genes. By analyzing ... [more] |
ME2022-88 SIP2022-7 pp.9-11 |
ME, SIP, TOKAI |
2022-12-07 13:35 |
Aichi |
(Primary: On-site, Secondary: Online) |
Skeleton Estimation for Swing based on Deep Model by Introducing Articulation Constraints into Training Atsuki Sakata, Shogo Kihira, Nobutaka Shimada (Ritsumeikan Univ.), Yuki Nagano, Masahiki Ueda (SRI) |
For the purpose of developing the automatic diagnosis system of players' golf swing, we propose a method for estimating ... [more] |
ME2022-91 SIP2022-10 pp.23-26 |
ME, SIP, TOKAI |
2022-12-07 15:00 |
Aichi |
(Primary: On-site, Secondary: Online) |
Comparison of gazing points and gaze prediction of midfielders in soccer training
-- for professional and college student soccer players -- Ryo Isa, Kyosuke Horio, Tsubasa Hirakawa, Takayoshi yamashita, Hironobu Fujiyoshi (Chubu Univ.) |
Gaze behavior in sports has received widespread attention. The purpose is to quantitatively analyze and compare the eye ... [more] |
ME2022-94 SIP2022-13 pp.35-38 |
BCT, IEICE-SIS |
2022-10-14 10:00 |
Aomori |
Hachinohe Institute of Technology (Primary: On-site, Secondary: Online) |
Robust Semi-Supervised Learning for Noisy Labels Using Early-learning Regularization and Weighted Loss Ryota Higashimoto, Soh Yoshida, Mitsuji Muneyasu (Kansai Univ.) |
Training Deep Neural Networks (DNNs) on datasets with incorrect labels (label noise) is an important challenge. In the p... [more] |
|
IEICE-SIP, IEICE-BioX, IEICE-IE, IEICE-MI, IST, ME [detail] |
2022-05-19 09:40 |
Kumamoto |
Kumamoto University (Primary: On-site, Secondary: Online) |
Variational Autoencoders Conditioned by Contrastive Features as Style-Feature Extractors Suguru Yasutomi, Toshihisa Tanaka (TUAT) |
Extracting style features is crucial for investigating the characteristics of data. This paper proposes a variational au... [more] |
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