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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| IBISML | 2020-03-11 10:10 |
Kyoto | Kyoto University (Cancelled but technical report was issued) |
Sentence Visualization Based on Relative Sentence Embeddings Haruya Ishizuka (Bridgestone Corp.), Daichi Mochihashi (ISM)  IBISML2019-42 |
Sentence visualization is important for a organization, such as company or government, since it facilitates to understan... [more] | IBISML2019-42 pp.63-70 |
| IBISML | 2020-03-11 11:35 |
Kyoto | Kyoto University (Cancelled but technical report was issued) |
Pre-training for Action Classification Task Using Video Frame Prediction Task Hidemoto Nakada, Hideki Asoh (AIST) IBISML2019-45 |
Continuous Video frames have strongly correlated with each other and thus include rich information that could be leverag... [more] | IBISML2019-45 pp.85-90 |
| HIP | 2019-12-20 09:00 |
Miyagi | RIEC, Tohoku University | Changes in the impression of urgency-inducing speech due to disaster education video Masahiro Yamataka (AUT), Takeshi Shibutani, Shuichi Sakamoto, Yoichi Suzuki, Toshiaki Muramoto (Tohoku Univ.) HIP2019-72 |
A function of the human mind called "normalcy bias" is known as a factor to prevent residents from evacuating when, e.g.... [more] | HIP2019-72 pp.41-46 |
| NLC, IPSJ-DC | 2019-09-28 16:00 |
Tokyo | Future Corporation | A comparison of Japanese pretrained BERT models Naoki Shibayama, Rui Cao, Jing Bai, Wen Ma, Hiroyuki Shinnou (Ibaraki Univ.) NLC2019-24 |
BERT is useful pre-training method for neural languages. There are pre-trained models for English which was used in a pa... [more] | NLC2019-24 pp.89-92 |
| PRMU, IBISML, IPSJ-CVIM [detail] | 2018-09-21 13:30 |
Fukuoka | [Short Paper]
Sekitoshi Kanai (NTT/Keio Univ.), Yasuhiro Fujiwara (NTT), Shuichi Adachi (Keio Univ.) PRMU2018-61 IBISML2018-38 |
(To be available after the conference date) [more] | PRMU2018-61 IBISML2018-38 pp.155-156 |
|
| NLP | 2014-07-01 10:00 |
Miyagi | Tohoku Univ. | Learning Restricted Boltzmann Machine with discrete learning parameter Seitaro Shinagawa (Tohoku Univ.), Yoshihiro Hayakawa (SNCT), Shigeo Sato, Takeshi Onomi, Koji Nakajima (Tohoku Univ.) NLP2014-27 |
Recently, the method of Deep Neural Network (DNN) with hierarchical learning has been remarkable for performance to solv... [more] | NLP2014-27 pp.37-40 |
| PRMU | 2014-03-14 15:30 |
Tokyo | Experimental study on effect of pre-training in deep learning through visualization of unit outputs Tsubasa Ochiai (Doshisha Univ./NICT), Hideyuki Watanabe (NICT), Shigeru Katagiri, Miho Ohsaki (Doshisha Univ.), Shigeki Matsuda, Chiori Hori (NICT) PRMU2013-210 |
To clarify the capability of recent powerful classifier concept, Deep Neural Networks (DNN), we experimentally investig... [more] |
PRMU2013-210 pp.253-258 |
|
| ITE-HI, ITE-AIT, ITE-ME, IE, ITS | 2008-02-19 10:25 |
Hokkaido | Graduate School of Information Science and Technology Hokkaido Univ | Near Duplicated Image Detection by Learning with Difference Vector to Original Image Toshiyuki Sano, Gou Hosoya, Hideki Yagi, Shigeichi Hirasawa (Waseda Univ.) ITS2007-62 IE2007-245 |
In this paper, a new pre-trained detection scheme for near-duplicated images is proposed.By using the assumption that th... [more] | ITS2007-62 IE2007-245 pp.1-6 |
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