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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| RCS, SAT (Joint) |
2023-08-31 10:55 |
Nagano | Naganoken Nokyo Building, and online (Primary: On-site, Secondary: Online) |
A study on source data and decoder of multitask CSI feedback method in FDD Massive MIMO Mayuko Inoue, Tomoaki Ohtsuki (Keio Univ.)  RCS2023-102 |
In frequency-division duplex (FDD) massive multiple-input multiple-output (MIMO) systems, it is necessary to obtain down... [more] | RCS2023-102 pp.5-8 |
| CQ, MIKA (Joint) |
2023-08-31 16:20 |
Fukushima | Tenjin-Misaki Sports Park | Enhancing Communication Efficiency for UAV Networks through Knowledge Distillation and Transfer Learning in Federated Learning Yalong Li, Zhaoyang Du, Celimuge Wu, Tsutomu Yoshinaga (UEC) CQ2023-30 |
Federated learning (FL) in unmanned aerial vehicles (UAVs) networks demands considerable communication resources to tran... [more] | CQ2023-30 pp.26-31 |
| MSS, CAS, SIP, VLD | 2023-07-06 10:40 |
Hokkaido | (Primary: On-site, Secondary: Online) |
Autoencoder Based Incremental LSI Test Escape Detection Using Transfer Learning Ayano Takaya, Michihiro Shintani (KIT) CAS2023-4 VLD2023-4 SIP2023-20 MSS2023-4 |
Machine-learning-based test escape detection is gaining attention as a novel approach for detecting faulty large-scale i... [more] | CAS2023-4 VLD2023-4 SIP2023-20 MSS2023-4 pp.16-21 |
| SC | 2023-06-03 10:35 |
Fukushima | UBIC 3D Theater, University of Aizu (Primary: On-site, Secondary: Online) |
[Poster Presentation]
Understanding transfer learning for medical image classification. Dao Ngoc HOng, Paik Incheon (UoA) SC2023-9 |
Transfer learning is one of the critical solutions to deal with the problem of data scarcity, where the learning process... [more] | SC2023-9 pp.48-52 |
| NC, MBE (Joint) |
2023-03-13 16:30 |
Tokyo | The Univ. of Electro-Communications (Primary: On-site, Secondary: Online) |
Evaluation of the transfer of prediction ability between two reflexive eye movements responsible for dynamic visual field stabilization. Toshimi Yamanaka, Yutaka Hirata (Chubu univ.) NC2022-98 |
The optokinetic response (OKR) and the vestibulo-ocular reflex (VOR) are reflexive eye movements that are responsible fo... [more] | NC2022-98 pp.36-41 |
| PRMU, IBISML, IPSJ-CVIM [detail] | 2023-03-02 16:40 |
Hokkaido | Future University Hakodate (Primary: On-site, Secondary: Online) |
Does the class imbalance in the pre-training always adversely affect transfer learning performance? Shojun Nakayama (Toshiba) PRMU2022-89 IBISML2022-96 |
In this work, we studied how class-imbalance in the pre-training affect to the accuracy of the transfer learning. We div... [more] | PRMU2022-89 IBISML2022-96 pp.151-156 |
| SP, IPSJ-SLP, EA, SIP [detail] | 2023-03-01 11:40 |
Okinawa | (Primary: On-site, Secondary: Online) |
Predominant Instrument Recognition in Polyphonic Music Based on Transfer Learning with Vanilla ResNet-50 Lifan Zhong, Daisuke Saito, Nobuaki Minematsu (UTokyo) EA2022-114 SIP2022-158 SP2022-78 |
Instrument recognition is an active research field in MIR (Music Information Retrieval) and has great potential for real... [more] | EA2022-114 SIP2022-158 SP2022-78 pp.232-237 |
| EMM | 2023-01-26 09:55 |
Miyagi | Tohoku Univ. (Primary: On-site, Secondary: Online) |
On the Transferability of Adversarial Examples between Isotropic Network and CNN models Miki Tanaka (Tokyo Metropolitan Univ.), Isao Echizen (NII), Hitoshi Kiya (Tokyo Metropolitan Univ.) EMM2022-62 |
Deep neural networks are well known to be vulnerable to adversarial examples (AEs). In addition, AEs generated for a sou... [more] | EMM2022-62 pp.7-12 |
| EMM | 2023-01-26 11:05 |
Miyagi | Tohoku Univ. (Primary: On-site, Secondary: Online) |
[Invited Talk]
Sound Event Detection and Localization for Humanoid Robots Yong-Hwa Park (KAIST) EMM2022-64 |
Pursuing intelligent machines that recognize human’s condition and surrounding events autonomously, this lecture focuses... [more] | EMM2022-64 p.19 |
| AP, WPT (Joint) |
2023-01-20 11:15 |
Hiroshima | Hiroshima Institute of Technology (Primary: On-site, Secondary: Online) |
Optimization of residual energy of devices by controlling the path of wireless charging robots Toshiki Nishidani, Hiroshi Saito (UTokyo) WPT2022-27 |
Wireless charging to devices located at a distance provides convenient and reliable power supply. We focused on optimizi... [more] | WPT2022-27 pp.1-6 |
| HCGSYMPO (2nd) |
2022-12-14 - 2022-12-16 |
Kagawa | Onsite (Sunport Takamatsu) and Online (Primary: On-site, Secondary: Online) |
Classification method of room sound environment using spectrogram images and its real environment evaluation Shota Sano (KAIT), Azusa Takahashi, Keisuke Hasegawa (JSP), Yuusuke Kawakita, Tsuyoshi Miyazaki, Hiroshi Tanaka (KAIT) |
There are various sound sources in a room, and various applications such as monitoring a living situation can be expecte... [more] | |
| SIS | 2022-12-05 16:00 |
Osaka | (Primary: On-site, Secondary: Online) |
Accuracy Improvement of Real Image Classification by Style Transfer Using Training Data Created from 3DCG Takeru Inoue, Youichi Tomita (Meiji Univ.), Kouji Gakuta, Etsuji Yamada, Aoi Kariya (Digital Printing & Solutions), Masakazu Kinosada, Yujiro Kitaide (Shinsei Printing), Ryusuke Miyamoto (Meiji Univ.) SIS2022-30 |
In general, in order to achieve sufficient accuracy by machine learning in practical applications, training data appropr... [more] | SIS2022-30 pp.38-43 |
| ET | 2022-11-05 14:55 |
Online | Online | Adaptive Prediction of Learners' Responses Considering Question Texts Yo Ehara (TGU) ET2022-37 |
This paper proposes a method for response prediction adaptive to learners which considers the texts of questions. [more] | ET2022-37 pp.39-46 |
| PRMU | 2022-09-14 16:15 |
Kanagawa | (Primary: On-site, Secondary: Online) |
Data Augmentation with Style Transfer for Fossil Image Segmentation Akihiro Waza (Osaka Metropolitan Univ.), Yuya Inamura (Osaka Prefecture Univ.), Katsufumi Inoue, Michifumi Yoshioka, Toshihiro Yamada (Osaka Metropolitan Univ.) PRMU2022-17 |
Fossils are extremely important materials in evolutionary biology and earth science. However, it is necessary to have sp... [more] | PRMU2022-17 pp.43-48 |
| AP, MW (Joint) |
2022-09-15 15:05 |
Ehime | The Museum of Art, EHIME (Primary: On-site, Secondary: Online) |
Radio Propagation Modeling with Few Data using Fine-Tuning Tatsuya Nagao, Takahiro Hayashi (KDDI Research) AP2022-82 |
Wireless communication systems, such as Beyond 5G, are expected to be essential social infrastructure, and numerous devi... [more] | AP2022-82 pp.62-67 |
| SWIM, SC | 2022-08-26 11:05 |
Online | Held online | Object Recognition by Fingertip Gestures Utilizing Transfer Learning of YOLOv5 Tsukasa Kudo (SIST) SWIM2022-12 SC2022-18 |
In object recognition for videos and images, when the target area is small, the area is firstly extracted by object dete... [more] | SWIM2022-12 SC2022-18 pp.9-15 |
| NS, SR, RCS, SeMI, RCC (Joint) |
2022-07-15 15:05 |
Ishikawa | The Kanazawa Theatre + Online (Primary: On-site, Secondary: Online) |
A Predictive Model of Heat Stress Using Heart Rate Variability Analysis Yusuke Shimada, Masashi Sugano (Osaka Metro. Univ.) SeMI2022-47 |
Predicting and controlling heat stress leads to comfort. Because People have different feelings against heat, we need a ... [more] | SeMI2022-47 pp.127-132 |
| RCS | 2022-06-17 13:40 |
Okinawa | University of the Ryukyus, Senbaru Campus and online (Primary: On-site, Secondary: Online) |
Evaluation of Source Data Selection for CSI Feedback Method based on Deep Transfer Learning in FDD Massive MIMO Systems Mayuko Inoue, Tomoaki Ohtsuki (Keio Univ) RCS2022-62 |
In frequency division duplexing (FDD) massive multiple-input multiple-output (MIMO), the downlink channel state informat... [more] | RCS2022-62 pp.224-229 |
| PRMU, IPSJ-CVIM | 2022-05-13 10:15 |
Aichi | Toyota Technological Institute | Shape-preserving Style Transfer by Dense Pixel Correspondences between Input and Output Images and its Application to Gaze Estimation Daiki Mushiake, Norimichi Ukita (TTI) PRMU2022-2 |
Gaze estimation has been applied to a variety of tasks， and many methods using deep learning have been proposed in recen... [more] | PRMU2022-2 pp.6-11 |
| SS | 2022-03-07 15:15 |
Online | Online | Project-domain adaptation with RoBERTa Model for Code Completion Daisuke Fukumoto, Toshiki Hirao (NAIST), Kenji Fujiwara (TCU), Hajimu Iida (NAIST) SS2021-50 |
Code completion is a function that automatically recommends code for developers when they are writing code. Code complet... [more] | SS2021-50 pp.49-53 |
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