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All Technical Committee Conferences (All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| SP, IPSJ-MUS, IPSJ-SLP [detail] | 2022-06-17 15:00 |
Online | Online | (To be available after the conference date) [more] | ||
| SP, IPSJ-MUS, IPSJ-SLP [detail] | 2022-06-17 15:00 |
Online | Online | Study of End-to-End Text-to-Speech that can seamlessly control speaker's individuality by Manipulating Speaker features Naoki Aotani, Sunao Hara, Msanobu Abe (Okayama Univ) |
(To be available after the conference date) [more] | |
| CAS, SIP, VLD, MSS | 2022-06-16 14:40 |
Aomori | Hachinohe Institute of Technology (Primary: On-site, Secondary: Online) |
Adversarial Robustness of Secret Key-Based Defenses against AutoAttack Miki Tanaka, April Pyone MaungMaung (Tokyo Metro Univ.), Isao Echizen (NII), Hitoshi Kiya (Tokyo Metro Univ.) |
(To be available after the conference date) [more] | |
| CCS, NLP | 2022-06-09 15:20 |
Osaka | (Primary: On-site, Secondary: Online) |
Speeding-up by Reduction of Processing Paths in Octave Convolution Akito Yoshikawa, Hidehiro Nakano (Tokyo City Univ.) |
(To be available after the conference date) [more] | |
| SIS, IPSJ-AVM | 2022-06-09 15:00 |
Fukuoka | KIT(Wakamatsu Campus) (Primary: On-site, Secondary: Online) |
[Invited Talk]
Advanced applications of machine learning techniques towards high-performance and cost-effective visual inspection AI Terumasa Tokunaga (Kyutech) |
(To be available after the conference date) [more] | |
| CCS, NLP | 2022-06-09 17:15 |
Osaka | (Primary: On-site, Secondary: Online) |
Visualization of decisions from CNN models trained on OpenStreetMap images labeled based on traffic accident data Kaito Arase, Zhijian Wu, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) |
(To be available after the conference date) [more] | |
| 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) |
(To be available after the conference date) [more] | |
| SC | 2022-05-27 09:55 |
Online | Online | Considerations for Identifying Machine Learning Models Naoto Kiribuchi, Ryohei Suzuki, Nami Ashizawa (NTT), Tetsushi Ohki, Hiroshi Mineno, Masakatsu Nishigaki (Shizuoka Univ.)  SC2022-2 |
As a part of considerations for identifying machine learning models, we experimented whether we can identify multiple di... [more] | SC2022-2 pp.7-12 |
| SC | 2022-05-27 13:25 |
Online | Online | Improvement of Performance of Question and Answering System using Ontology Generation Ayato Kuwana, Incheon Paik (UoA) SC2022-7 |
Automating ontology generation from raw text corpus is required to meet the ontology demand. As an initial attempt of on... [more] | SC2022-7 pp.37-42 |
| SIP, BioX, IE, MI, ITE-IST, ITE-ME [detail] | 2022-05-19 16:10 |
Kumamoto | Kumamoto University Kurokami Campus (Primary: On-site, Secondary: Online) |
[Invited Talk]
Image and Video Restoration with Deep Learning Satoshi Iizuka (Univ. of Tsukuba) SIP2022-15 BioX2022-15 IE2022-15 MI2022-15 |
In this talk, I will introduce techniques for restoring black-and-white images and videos with high accuracy using deep ... [more] | SIP2022-15 BioX2022-15 IE2022-15 MI2022-15 p.78 |
| SIP, BioX, IE, MI, ITE-IST, ITE-ME [detail] | 2022-05-20 16:40 |
Kumamoto | Kumamoto University Kurokami Campus (Primary: On-site, Secondary: Online) |
3D Medical Image Segmentation Using 2.5D Deformable Convolutional CNN Yuya Okumura, Kudo Hiroyuki, Takizawa Hotaka (Tsukuba Univ.) SIP2022-29 BioX2022-29 IE2022-29 MI2022-29 |
An effective method to improve the accuracy of 3D medical image segmentation using deep learning is to use deformable co... [more] | SIP2022-29 BioX2022-29 IE2022-29 MI2022-29 pp.150-155 |
| SIP, BioX, IE, MI, ITE-IST, ITE-ME [detail] | 2022-05-20 17:00 |
Kumamoto | Kumamoto University Kurokami Campus (Primary: On-site, Secondary: Online) |
Deformable registration of 3D medical images with Deep Residual UNet Taiga Nakamura, Yuki Sato, Hiroyuki Kudo, Hotaka Takizawa (Univ. of Tsukuba) SIP2022-30 BioX2022-30 IE2022-30 MI2022-30 |
(To be available after the conference date) [more] | SIP2022-30 BioX2022-30 IE2022-30 MI2022-30 pp.156-160 |
| EA | 2022-05-13 16:25 |
Online | Online | Study on noise reduction with a single noisy speech based on Double-DIP Hien Oonaka (NITTC), Takuya Fujimura (Nagoya Univ.), Ryoichi Miyazaki (NITTC) EA2022-12 |
This paper proposes a new noise reduction method with an untrained Deep Neural Network ( DNN) for a single noisy speech.... [more] | EA2022-12 pp.54-61 |
| PRMU, IPSJ-CVIM | 2022-05-13 10:00 |
Aichi | Toyota Technological Institute | Robust Small Objects Detection Using YOLO-v4 with Attention and Layer Yuedong Li (Chuo Univ) PRMU2022-1 |
Abstract: It is a difficult problem how to make traditional neural network algorithm show good adaptability to the typic... [more] | PRMU2022-1 pp.1-5 |
| PRMU, IPSJ-CVIM | 2022-05-13 10:45 |
Aichi | Toyota Technological Institute | Efficient DNN model for word lip-reading Daiki Arakane, Takeshi Saitoh (Kyutech) PRMU2022-4 |
This paper studies various deep learning models for lip-reading technology, including one of supervised learning of the ... [more] | PRMU2022-4 pp.18-23 |
| NS | 2022-04-15 11:10 |
Tokyo | kikai shinkou kaikan + online (Primary: On-site, Secondary: Online) |
Service Chaining Based on Capacitated Shortest Path Tour Problem
-- Solution Based on Deep Reinforcement Learning and Graph Neural Network -- Takanori Hara, Masahiro Sasabe (NAIST) NS2022-2 |
The service chaining problem is one of the resource allocation problems in network functions virtualization (NFV) networ... [more] | NS2022-2 pp.7-12 |
| PRMU, IPSJ-CVIM | 2022-03-11 10:45 |
Online | Online | Self-supervised Contrastive Learning Using Triplet Loss for Offline Recognition of Handwritten Chinese Text lines Trung Tan Ngo, Hung Tuan Nguyen, Masaki Nakagawa (TUAT) PRMU2021-78 |
In this paper, we propose a framework for contrastive learning of visual representations using online triplet loss and a... [more] | PRMU2021-78 pp.115-120 |
| CQ, IMQ, MVE, IE (Joint) [detail] |
2022-03-09 10:10 |
Online | Online (Zoom) | A study on player and ball tracking in tennis videos. Kosuke Matsumoto (Kobe univ.), Junki Tamae (iret), Nobutaka Kuroki (Kobe univ.), Kensuke Hirano (iret), Masahiro Numa (Kobe univ.) IMQ2021-16 IE2021-78 MVE2021-45 |
This paper proposes a player and ball tracking method in tennis videos with image processing techniques. The proposed me... [more] | IMQ2021-16 IE2021-78 MVE2021-45 pp.33-38 |
| IBISML | 2022-03-08 13:05 |
Online | Online | [Invited Talk]
--- Takashi Matsubara (Osaka Univ.) IBISML2021-34 |
Deep learning is being considered as the most promising approach to building an artificial intelligence (AI) system; it ... [more] | IBISML2021-34 p.27 |
| IBISML | 2022-03-09 10:15 |
Online | Online | [Invited Talk]
--- Takahiro Tsukahara (Tokyo University of Science) IBISML2021-41 |
Turbulence of viscoelastic fluids, such as dilute polymer/surfactant solutions, is of practical importance, because it c... [more] | IBISML2021-41 p.34 |
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