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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 100  /  [Next]  
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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