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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| MI | 2024-03-04 12:40 |
Okinawa | OKINAWAKEN SEINENKAIKAN (Primary: On-site, Secondary: Online) |
Teeth Segmentation from 3D Dental Model using Deep Learning and Statistical Shape Models Hazuki Yamada, Kana Kono (Okayama Univ.), Shoko Miyauchi (Kyushu Univ.), Hiroshi Kamioka (Okayama Univ.), Ken'ichi Morooka (Kumamoto Univ.)  MI2023-73 |
3D dental model generated by using an intraoral scanner is a useful tool for knowing the shape of teeth. The application... [more] | MI2023-73 pp.133-136 |
| MI | 2023-03-06 14:07 |
Okinawa | OKINAWA SEINENKAIKAN (Primary: On-site, Secondary: Online) |
Application of statistical shape modeling of whole lower limbs in the prediction of musculoskeletal shapes Yuto Masaki, Yoshito Otake, Mazen Soufi, Yi Gu (NAIST), Keisuke Uemura (Osaka Univ), Masaki Takao (Ehime Univ.), Takuma Miyamoto, Yasuhito Tanaka (Nara Medical Univ), Seiji Okada, Nobuhiko Sugano (Osaka Univ), Yoshinobu Sato (NAIST) MI2022-84 |
Musculoskeletal modeling of the whole lower limbs that reflects patient-specific anatomical features is important in bio... [more] | MI2022-84 pp.57-62 |
| EA, US (Joint) |
2022-12-22 16:50 |
Hiroshima | Satellite Campus Hiroshima | [Poster Presentation]
Data augmentation method for machine learning on speech data Tsubasa Maruyama (Tokyo Tech), Tsutomu Ikegami (AIST), Toshio Endo (Tokyo Tech), Takahiro Hirofuchi (AIST) EA2022-68 |
In machine learning, data augmentation is a method to enhance the number and diversity of data by adding transformations... [more] | EA2022-68 pp.42-48 |
| IE, ITS, ITE-AIT, ITE-ME, ITE-MMS [detail] | 2022-02-21 15:50 |
Online | Online | Statistical Analysis on Estimation of Laparoscopic Image Region of Interest Including Contrast Enhancement Based on Saliency Map Norifumi Kawabata (Hokkaido Univ.), Toshiya Nakaguchi (Chiba Univ.) ITS2021-34 IE2021-43 |
In the medical field such as hospital, there are many chance for medical workers to see medical images visually. Therefo... [more] | ITS2021-34 IE2021-43 pp.55-60 |
| NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] | 2021-06-28 16:10 |
Online | Online | More Powerful and General Selective Inference for Stepwise Feature Selection using Homotopy Method Kazuya Sugiyama (Nitech), Vo Nguyen Le Duy, Ichiro Takeuchi (Nitech/RIKEN) NC2021-8 IBISML2021-8 |
Conditional selective inference (SI) has been actively studied as a new statistical inference framework for data-driven ... [more] | NC2021-8 IBISML2021-8 pp.55-61 |
| SP, IPSJ-SLP, IPSJ-MUS | 2021-06-19 15:00 |
Online | Online | Simulation of Body-conducted Speech and Synthesis of One's Own Voice with a Sound-proof Earmuff and Bone-conduction Microphones Chen Ruiyan, Nishimura Tazuko, Minematsu Nobuaki, Saito Daisuke (UTokyo) SP2021-15 |
When one hears his/her recorded voices for the first time, s/he is probably surprised and not rarely disappointed at the... [more] | SP2021-15 pp.63-68 |
| SP | 2020-01-29 11:30 |
Toyama | Application of Deep Gaussian Process to Multi-Speaker Text-to-Speech Synthesis using Speaker Codes Kentaro Mitsui, Tomoki Koriyama, Hiroshi Saruwatari (UTokyo) SP2019-49 |
Speaker codes are widely used to achieve multi-speaker text-to-speech synthesis. Conventionally, Deep Neural Network (D... [more] |
SP2019-49 pp.31-36 |
|
| IBISML | 2020-01-09 14:15 |
Tokyo | ISM | Statistical Learning Theory of Data changed in Value Satoshi Kataoka (Titech) IBISML2019-21 |
In Statistical Learning Theory, the accuracy of inference is evaluated by generalization loss or free energy of true d... [more] |
IBISML2019-21 pp.25-30 |
| IA | 2019-11-29 11:30 |
Aomori | Tsugaru Densho Kougei-kan | Development and Evaluation of Wide-Area Sensing System Utilizing Fixed Route Bus Tomoya Kimura, Hiroshi Yamamoto (Ritsumeikan Univ.) IA2019-44 |
After occurrence of a ceiling board collapse accident in Chuo Expressway Sasago Tunnel in 2012, local governments managi... [more] | IA2019-44 pp.7-12 |
| QIT (2nd) |
2019-05-21 11:40 |
Fukuoka | Kyushu University, Chikushi Campus | Directed-completeness of statistical experiments and channels on operator algebras Yui Kuramochi (Univ. Tokyo) |
For statistical experiments or quantum channels on von Neumann algebras, we introduce a preorder (equivalence) relati... [more] |
|
| SS | 2019-03-04 10:15 |
Okinawa | Statistical model checking of hybrid systems with Acumen Kosuke Inoue, Daisuke Ishii (Fukui Univ.) SS2018-54 |
An integrated tool for modeling, simulation and verification is useful for developing reliable continuous/discrete hybri... [more] | SS2018-54 pp.13-18 |
|
| SP | 2019-01-27 10:40 |
Ishikawa | Kanazawa-Harmonie | Evaluation of end-to-end speech synthesis method using speaking styles Kiyoshi Kurihara, Nobumasa Seiyama, Tadashi Kumano, Atsushi Imai (NHK) SP2018-58 |
The purpose of this study was to conduct end-to-end text-to-speech synthesis in Japanese; we developed a system that use... [more] | SP2018-58 pp.29-34 |
| NLC, IPSJ-NL, SP, IPSJ-SLP (Joint) [detail] |
2018-12-10 16:30 |
Tokyo | Waseda Univ. Nishiwaseda Campus | Evaluation of Japanese end-to-end speech synthesis method inputting kana and prosodic symbols Kiyoshi Kurihara, Nobumasa Seiyama, Tadashi Kumano, Atsushi Imai (NHK) SP2018-49 |
The purpose of this study was to conduct end-to-end text-to-speech synthesis in Japanese; we developed a system that use... [more] | SP2018-49 pp.89-94 |
| QIT (2nd) |
2018-11-26 10:30 |
Tokyo | The University of Tokyo | Statistical Independence and Zero Correlation: Classical and Quantum Toru Ohira (Nagoya Univ.) |
We normally perceive quantum phenomena as ``strange'' which do not match our classical intuitions. Here, we intentionall... [more] | |
| SDM | 2018-10-18 14:00 |
Miyagi | Niche, Tohoku Univ. | Statistical Analysis of Electric Characteristics Variability Using MOSFETs with Asymmetric Source and Drain Shinya Ichino, Akinobu Teramoto, Rihito Kuroda, Takezo Mawaki, Tomoyuki Suwa, Shigetoshi Sugawa (Tohoku Univ.) SDM2018-62 |
In this paper, a statistical analysis of electric characteristics variabilities such as threshold voltage variability an... [more] | SDM2018-62 pp.51-56 |
| SWIM, SC | 2018-08-24 15:45 |
Tokyo | Housei Univ. | Experimental report of effects of stock price fluctuation statistics on candlestick chart synthesis Yoshihisa Udagawa (Tokyo Polytechnic Univ.) SWIM2018-14 SC2018-21 |
Extracting stock price change patterns and predicting future stock prices are an interesting task for traders as well as... [more] | SWIM2018-14 SC2018-21 pp.39-44 |
| PRMU, SP | 2018-06-29 11:00 |
Nagano | Speaker adaptation in speech synthesis based on neural networks including temporal structure modeling Kento Nakao, Kei Hashimoto, Keiichiro Oura, Yoshihiko Nankaku, Keiichi Tokuda (NIT) PRMU2018-31 SP2018-11 |
This paper proposes a speaker adaptation technique for speech synthesis based on deep neural networks (DNNs) using a str... [more] | PRMU2018-31 SP2018-11 pp.53-58 |
|
| PRMU, MI, IE, SIP | 2018-05-17 17:00 |
Gifu | [Invited Talk]
Statistical Modeling of 3-D DFT Coefficients of Moving Images and Its Applications to Video Restoration Takahiro Saito, Takashi Komatsu (Kanagawa Univ.) SIP2018-6 IE2018-6 PRMU2018-6 MI2018-6 |
Recently we have presented moving-image denoising with 3-D Mean-Separation-type Short-Time DFT and demonstrated that it ... [more] | SIP2018-6 IE2018-6 PRMU2018-6 MI2018-6 pp.23-28 |
|
| SIP, EA, SP, MI (Joint) [detail] |
2018-03-19 10:50 |
Okinawa | On the Use of Deep Gaussian Processes for GPR-based Speech Synthesis Tomoki Koriyama, Takao Kobayashi (Tokyo Inst. of Tech.) EA2017-106 SIP2017-115 SP2017-89 |
This paper proposes a speech synthesis framework based on deep Gaussian processes (DGPs). DGP is a Bayesian deep learn... [more] |
EA2017-106 SIP2017-115 SP2017-89 pp.27-32 |
|
| SIP, EA, SP, MI (Joint) [detail] |
2018-03-20 09:00 |
Okinawa | [Poster Presentation]
A Hybrid Approach on Electrolaryngeal Speech Enhancement based on Spectral Differential Features and Noise Suppression Mohammad Eshghi, Kazuhiro Kobayashi, Tomoki Toda (Nagoya Univ.) EA2017-141 SIP2017-150 SP2017-124 |
This work presents a hybrid approach for enhancing the quality of the electrolaryngeal (EL) speech. Current hybrid enhan... [more] | EA2017-141 SIP2017-150 SP2017-124 pp.221-226 |
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