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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| HCGSYMPO (2nd) |
2022-12-14 - 2022-12-16 |
Kagawa | Onsite (Sunport Takamatsu) and Online (Primary: On-site, Secondary: Online) |
Analysis of Heartbeats and Facial Expressions of Game Players
-- Toward Objective Measurement of QOL -- Hirotada Ueda, Kei Shimonishi, Kazuaki Kondo, Yuich Nakamura (Kyoto Univ.) |
An experiment was conducted to record and analyze heart rate data and facial images of players while playing a game in o... [more] | |
| IA, ICSS | 2022-06-24 10:25 |
Nagasaki | Univ. of Nagasaki (Primary: On-site, Secondary: Online) |
Application of Adversarial Examples to Physical ECG Signals Taiga Ono (Waseda Univ.), Takeshi Sugawara (UEC), Jun Sakuma (Tsukuba Univ./RIKEN), Tatsuya Mori (Waseda Univ./RIKEN/NICT)  IA2022-11 ICSS2022-11 |
This work aims to assess the reality and feasibility of applying adversarial examples to attack cardiac diagnosis system... [more] | IA2022-11 ICSS2022-11 pp.61-66 |
| 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 |
| KBSE | 2022-03-10 10:15 |
Online | Online (Zoom) | Safety risk analysis and evaluation method for DNN system in autonomous driving Tomoko Kaneko, Yuji Takahashi (NII), Shinichi Yamaguchi (SDM), Junji Hashimoto (GREE), Nobukazu Yoshioka (Soudai) KBSE2021-51 |
There is a great concern about the quality of current AI, especially DNN (deep learning), especially about its safety an... [more] | KBSE2021-51 pp.60-65 |
| EA, SIP, SP, IPSJ-SLP [detail] | 2022-03-01 12:20 |
Okinawa | (Primary: On-site, Secondary: Online) |
Training Algorithm for Multispeaker Text-To-Speech Synthesis Considering Adversarial Regularizer Yusuke Nakai, Kenta Udagawa, Yuki Saito, Hiroshi Saruwatari (UTokyo) EA2021-72 SIP2021-99 SP2021-57 |
(To be available after the conference date) [more] | EA2021-72 SIP2021-99 SP2021-57 pp.50-55 |
| VLD, DC, RECONF, ICD, IPSJ-SLDM (Joint) [detail] |
2021-12-01 09:20 |
Online | Online | Block Sparse MLP-based Vision DNN Accelerators on Embedded FPGAs Akira Jinguji, Hiroki Nakahara (Tokyo Tech) VLD2021-21 ICD2021-31 DC2021-27 RECONF2021-29 |
Since the advent of Vision Transformer, a deep learning model for image recognition without Convolution, MLP-based model... [more] | VLD2021-21 ICD2021-31 DC2021-27 RECONF2021-29 pp.25-30 |
| EMM, EA, ASJ-H | 2021-11-15 09:00 |
Online | Online | [Poster Presentation]
A Study on Convergency of DNN Watermarking without Embedding Loss Function Takuro Tanaka, Tatsuya Yasui, Minoru Kuribayashi, Nobuo Funabiki (Okayama Univ.) EA2021-35 EMM2021-62 |
Intellectual Property Rights protection related to Deep Neural Networks is an important issue due to the high cost of tr... [more] | EA2021-35 EMM2021-62 pp.49-54 |
| RISING (3rd) |
2021-11-16 11:30 |
Tokyo | (Primary: On-site, Secondary: Online) |
Throughput Prediction by Radio Environment Correlation Recognition Using Crowd Sensing and Federated Learning Satoshi Nakaniida, Takeo Fujii (UEC) |
We propose an approach using federated learning for predicting Wi-Fi and LTE transmission control protocol (TCP) through... [more] | |
| SR | 2021-11-05 11:15 |
Online | Online | Throughput Prediction by Radio Environment Correlation Recognition Using Crowd Sensing and Federated Learning Satoshi Nakaniida, Takeo Fujii (UEC) SR2021-53 |
We propose an approach using federated learning for predicting Wi-Fi and LTE transmission control protocol (TCP) through... [more] | SR2021-53 pp.72-78 |
| SP, WIT, IPSJ-SLP, ASJ-H [detail] | 2021-10-19 15:10 |
Online | Online | A study on model training for DNN-HSMM-based speech synthesis using a large-scale speech corpus Nobuyuki Nishizawa, Gen Hattori (KDDI Research) SP2021-34 WIT2021-27 |
In this study, an investigation into model training for DNN-HSMM-based speech synthesis using a large speech corpus coll... [more] | SP2021-34 WIT2021-27 pp.52-57 |
| SIS, ITE-BCT | 2021-10-07 15:05 |
Online | Online | A Method for Generating Pseudo-Captured Images to Evaluate the Performance of Data Embedding Techniques to Printed Images Using Mobile Devices Masahiro Yasuda, Mitsuji Muneyasu, Soh Yoshida (Kansai Univ.) SIS2021-15 |
A data-embedding technique to printed images has been proposed. In this technique, the embedded data is retrieved from t... [more] | SIS2021-15 pp.29-34 |
| PRMU, IPSJ-CVIM | 2020-05-14 13:30 |
Online | Online | Human Action Recognition with Two-stream 3D BagNet Junya Uchida, Yu Wang, Jien Kato (Ritsumeikan Univ.) PRMU2020-3 |
We propose the Two-stream 3D BagNet for the human action recognition task. The proposed architecture is inspired by the ... [more] | PRMU2020-3 pp.13-17 |
| PRMU, IPSJ-CVIM | 2020-03-17 16:00 |
Kyoto | (Cancelled but technical report was issued) |
Acceleration of Deep Learning Inference by Model Cascading Shohei Enomoto, Takeharu Eda (NTT) PRMU2019-98 |
In recent years, various applications have appeared due to the development of deep learning and the spread of IoT device... [more] | PRMU2019-98 pp.203-208 |
| IE, IMQ, MVE, CQ (Joint) [detail] |
2020-03-06 10:10 |
Fukuoka | Kyushu Institute of Technology (Cancelled but technical report was issued) |
A Comparison Study of Neural Sign Language Translation Methods with Spatio-Temporal Features Kodai Watanabe, Wataru Kameyama (Waseda Univ.) IMQ2019-68 IE2019-150 MVE2019-89 |
In Neural Sign Language Translation, a model based on 2DCNN (2 Dimensional Convolutional Neural Network) called AlexNet ... [more] | IMQ2019-68 IE2019-150 MVE2019-89 pp.273-278 |
| 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 |
| SP, EA, SIP | 2020-03-03 09:00 |
Okinawa | Okinawa Industry Support Center (Cancelled but technical report was issued) |
[Poster Presentation]
Automatic estimation of prosodic control made in English utterances using DNN-based acoustic models trained with prosodic features and labels Yang Shen, Shintarou Ando, Nobuaki Minematsu, Daisuke Saito (UTokyo), Satoshi Kobashikawa (NTT) EA2019-136 SIP2019-138 SP2019-85 |
This paper investigate how to utilize DNN acoustic models trained with prosodic features and labels to detect prosodic e... [more] | EA2019-136 SIP2019-138 SP2019-85 pp.201-206 |
| ICSS, IPSJ-SPT | 2020-03-03 11:40 |
Okinawa | Okinawa-Ken-Seinen-Kaikan (Cancelled but technical report was issued) |
Adversarial Attacks against Electrocardiograms Taiga Ono (Waseda Univ.), Takeshi Sugawara (UEC), Tatsuya Mori (Waseda Univ.) ICSS2019-90 |
Recent advancements in clinical services powered by deep learning have been met with the threat of Adversarial Examples.... [more] | ICSS2019-90 pp.131-136 |
| CQ, CBE (Joint) |
2020-01-17 14:00 |
Tokyo | NHK Science & Technology Research Laboratories | A study sound source separation method for recorded multiple sounds Satoru Jomae, Kenko Ota, Hideaki Yoshino (NIT) CQ2019-131 |
It is useful to separate multiple sounds into single sounds in order to improve the accuracy of fundamental frequency an... [more] | CQ2019-131 pp.137-140 |
| EA | 2019-12-12 15:00 |
Fukuoka | Kyushu Inst. Tech. | Fundamental Study on Sound Source exploration method inside structure using DNN and CAE Shunsuke Kita (ORIST), Yoshinobu Kajikawa (Kansai Univ.) EA2019-71 |
Currently, it has become possible to estimate the position of the sound source concerning the direct sound by the sound ... [more] | EA2019-71 pp.37-44 |
| NLC, IPSJ-NL, SP, IPSJ-SLP (Joint) [detail] |
2019-12-06 16:00 |
Tokyo | NHK Science & Technology Research Labs. | A comparison of neural vocoders in singing voice synthesis Sota Wada, Yukiya Hono, Shinji Takaki, Kei Hashimoto, Keiichiro Oura, Yoshihiko Nankaku, Keiichi Tokuda (Nagoya Inst. of Tech.) SP2019-42 |
In this study, we compare five types of vocoders based on neural networks (neural vocoders) for singing voice synthesis.... [more] | SP2019-42 pp.85-90 |
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