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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| MVE | 2023-09-07 13:25 |
Osaka | (Primary: On-site, Secondary: Online) |
A preliminary attempt to infer sustained attentional state based on electroencephalography Mirei Hayashi, Masayuki Hayashi (NUT), Sae Kawasaki, Takumi Okubo, Yuta Hino, Norimichi Tsumura (Chiba Univ), Hirokazu Doi (NUT)  MVE2023-16 |
To promote learning efficiency in educational activities, it is crucial to maintain concentration of learners. As a pre... [more] |
MVE2023-16 pp.11-14 |
| NC, NLP | 2023-01-29 15:05 |
Hokkaido | Future University Hakodate (Primary: On-site, Secondary: Online) |
Predictions and Attentions Acquired by Vision Transformer with Source-Target Attention from Dilated Convolutions on Small Data Sets Tatsuki Shimura, Katsumi Tadamura, Toshikazu Samura (Yamaguchi Univ) NLP2022-104 NC2022-88 |
Vision Transformer (ViT) requires large data sets during pre-training phase to acquire high classification accuracy on a... [more] | NLP2022-104 NC2022-88 pp.123-128 |
| NC, NLP | 2023-01-29 15:55 |
Hokkaido | Future University Hakodate (Primary: On-site, Secondary: Online) |
Indoor air quality prediction using multi-reservoir echo state network with attention mechanism Wenrui Qiu, Gouhei Tanaka (UTokyo) NLP2022-106 NC2022-90 |
Indoor air quality (IAQ) is a critical matter of concern in terms of its impact on public health and well-being. Researc... [more] | NLP2022-106 NC2022-90 pp.135-140 |
| IMQ | 2022-12-16 15:55 |
Chiba | Nishi-Chiba Campus, Chiba Univ. | Improving Pedestrian Attribute Recognition with Spatial Attention and Attribute Correlation Yichen Chen, Tetsuya Matsumoto (Nagoya Univ.), Yoshinori Takeuchi (Daido Univ.), Hiroaki Kudo (Nagoya Univ.) IMQ2022-18 |
In the field of video surveillance, pedestrian attribute recognition is a focus technical thema of study. To predict cer... [more] | IMQ2022-18 pp.16-21 |
| PRMU, IPSJ-CVIM | 2022-05-13 10:30 |
Aichi | Toyota Technological Institute | Visualization of Decision Rationale Using Social and Physical Attention Mechanisms in Human Trajectory Prediction Model Masahiro Kato, Norimichi Ukita (TTI) PRMU2022-3 |
There is a great deal of interest in explainable AI that clarifies the basis of decisions, such as why a model makes a p... [more] | PRMU2022-3 pp.12-17 |
| PRMU | 2021-12-17 15:30 |
Online | Online | [Short Paper]
Prediction Model of Early Recurrence of Hepatocellular Carcinoma Based on Deep Learning with Attention Module Weibin Wang (Ritsumeikan Univ.), Fang Wang, Qingqing Chen (Zhejiang Univ.), Yutaro Iwamoto (Ritsumeikan Univ.), Xianhua Han (Yamaguchi Univ.), Yen-wei Chen (Ritsumeikan Univ.) PRMU2021-59 |
Early recurrence of hepatocyte carcinoma (HCC) will still lead to a decrease in the survival rate of patients who have a... [more] | PRMU2021-59 pp.195-198 |
| HIP | 2021-10-22 13:35 |
Online | Online | A saliency estimation model for drivers' egocentric vision movies considering self-motion velocity Yuya Homma, Masashi Fujita, Takeshi Kohama (Kindai Univ.) HIP2021-44 |
In order to predict where a driver’s attention should be directed during driving, Kodama et al. have developed a salienc... [more] | HIP2021-44 pp.75-80 |
| MICT, MI | 2020-11-04 11:20 |
Online | Online | Automatic Classification of Pancreatic Cancer and Analysis of Video Frames Using 3D CNN and Attention Sota Kato, Kazuhiro Hotta (Meijo Univ.), Hiroki Kawashima, Takuya Ishikawa, Hirotaka Suzuki (Nagoya Univ.) MICT2020-12 MI2020-38 |
The purpose of this research is to classify pancreatic cancer from videos and to analyze an important location for the c... [more] | MICT2020-12 MI2020-38 pp.24-28 |
| HCGSYMPO (2nd) |
2019-12-11 - 2019-12-13 |
Hiroshima | Hiroshima-ken Joho Plaza (Hiroshima) | Automatic Evaluation of Press Conferences Using LSTM with Self-Attention Mechanism Shengzhou Yi (UTokyo), Koshiro Mochitomi, Isao Suzuki (PRAP Japan, Inc.), Xueting Wang, Toshihiko Yamasaki (UTokyo) |
We proposed an approach to automatically predict the evaluation of consultants in press conferences using text only. The... [more] | |
| ITS, IE, ITE-MMS, ITE-HI, ITE-ME, ITE-AIT [detail] | 2019-02-20 10:15 |
Hokkaido | Hokkaido Univ. | A note on estimation of inspectors' visual attention using distress images of subway tunnels
-- Trial introduction of deep learning-based saliency prediction methods -- Ryota Saito, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
This paper presents the first trial for estimating inspectors' visual attention of distress images in subway tunnels. Th... [more] | |
| HCGSYMPO (2nd) |
2017-12-13 - 2017-12-15 |
Ishikawa | THE KANAZAWA THEATRE | Analysis of Head, Torso, and Hands Motions and Coordination Affected by Attention Distribution Takanori Kurisu, Kazuaki Kondo, Yuichi Nakamura (Kyoto Univ.) |
In this paper, we investigate human body behaviors affected by attention diversity for multiple objects.The analysis tar... [more] | |
| SP, IPSJ-SLP, NLC, IPSJ-NL (Joint) [detail] |
2016-12-20 09:55 |
Tokyo | NTT Musashino R&D | Hard-Attentional Neural Network Models for Emphasis Speech Translation Quoc Truong Do, Sakriani Sakti, Graham Neubig, Satoshi Nakamura (NAIST) SP2016-50 |
Traditional speech translation systems are oblivious to paralinguistic information. A recent work has tried to tackle th... [more] | SP2016-50 pp.7-8 |
| SSS | 2011-10-06 16:10 |
Tokyo | Ｋｉｋａｉ－Ｓｈｉｎｋｏ－Ｋａｉｋａｎ Ｂｌｄｇ | [Invited Talk]
Vehicle Technologies of Preparing for Unexpected Accidents Hiroshi Takahashi (Shonan Inst Tech) SSS2011-13 |
My focused issues are the driving events that are happened with unexpected prediction. For instance, the pedestrian that... [more] | SSS2011-13 pp.17-20 |
| MBE, NC (Joint) |
2010-11-18 10:50 |
Miyagi | Tohoku University | Using top-down attention based on 3D structure of scene to estimate the location of gaze Kohei Mashimo, Kazumichi Matsumiya, Ichiro Kuriki, Satoshi Shioiri (Tohoku Univ.) MBE2010-39 |
Models of visual attention shift have been proposed. Although an attention model can be applied to many uses, the abilit... [more] | MBE2010-39 pp.21-24 |
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