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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| AI | 2023-09-12 15:35 |
Hokkaido | Variational Autoencoder Oriented Protection for Intellectual Property Ryo Kumagai, Shu Takemoto, Yusuke Nozaki, Masaya Yoshikawa (Meijo Univ.)  AI2023-31 |
In recent years, generative AI, which generates images based on instructions in natural language, has developed rapidly ... [more] | AI2023-31 pp.180-186 |
|
| EA, SIP, SP, IPSJ-SLP [detail] | 2022-03-02 10:45 |
Okinawa | (Primary: On-site, Secondary: Online) |
Evaluation of sentence-level generation in Japanese dialect speech synthesis using accent latent variables Kazuya Yufune, Tomoki Koriyama, Shinnosuke Takamichi, Hiroshi Saruwatari (UTokyo) EA2021-79 SIP2021-106 SP2021-64 |
Japanese dialect speech synthesis is useful for personalized speech synthesis systems. However, inability to prepare acc... [more] | EA2021-79 SIP2021-106 SP2021-64 pp.96-101 |
| IT | 2021-07-09 13:00 |
Online | Online | Bayesian Optimal Prediction and Its Approximation Algorithm for the Difference of Response Variables with and without Measures Considering Individual Differences by Assuming Latent Clusters Taisuke Ishiwatari (Waseda Univ.), Shota Saito (Gunma Univ.), Toshiyasu Matsushima (Waseda Univ.) IT2021-23 |
In observational studies, there are problems such as "the measure can be given only once to the target" and "the charact... [more] | IT2021-23 pp.45-50 |
| NLP, NC (Joint) |
2020-01-24 10:10 |
Okinawa | Miyakojima Marine Terminal | Optimal Transport based Autoencoder for class and style Disentanglement Florian Tambon, Tetsuo Furukawa (Kyutech) NC2019-62 |
The Sinkhorn autoencoder is a novel generative model using optimal transport to model the aggregated posterior from samp... [more] | NC2019-62 pp.17-22 |
| MBE, NC (Joint) |
2011-11-24 16:10 |
Miyagi | ECEI Departments, Graduate School of Engineering, Tohoku University | An image restoration method for Poisson observation using a latent variational approximation Hayaru Shouno (UEC), Ken Takiyama, Masato Okada (The Univ. of Tokyo) NC2011-73 |
In this study, we treat an image restoration problem throughout a Poisson noise channel observation. The Poisson noise c... [more] | NC2011-73 pp.11-16 |
| IBISML | 2011-11-10 15:45 |
Nara | Nara Womens Univ. | Image Segmentation and Restoration using Switching State-Space Model and Variational Bayesian Method Ryota Hasegawa (Kansai Univ.), Ken Takiyama, Masato Okada (Univ. of Tokyo), Seiji Miyoshi (Kansai Univ.) IBISML2011-67 |
We derive a deterministic algorithm that restores and segments image using switching state-space model and variational B... [more] | IBISML2011-67 pp.169-174 |
| IBISML | 2011-11-10 15:45 |
Nara | Nara Womens Univ. | Image segmentation and restoration by variational Bayesian method and MCMC Kenta Kayano (Kansai Univ.), Kenji Nagata, Masato Okada (Univ. of Tokyo), Seiji Miyoshi (Kansai Univ.) IBISML2011-68 |
In this paper, we derive a deterministic algorithm that restores and segments an image by using variational Bayesian met... [more] | IBISML2011-68 pp.175-180 |
| IBISML | 2011-11-10 15:45 |
Nara | Nara Womens Univ. | A latent variational approximation method of Total variation for noise reduction Hayaru Shouno (UEC), Masato Okada (The Univ. of Tokyo) IBISML2011-74 |
(To be available after the conference date) [more] | IBISML2011-74 pp.217-222 |
| NC | 2011-07-26 11:00 |
Hyogo | Graduate School of Engineering, Kobe University | Image Segmentation and Restoration using Region-Based Hidden Variables and Belief Propagation Ryota Hasegawa (Kansai Univ.), Masato Okada (Univ. of Tokyo), Seiji Miyoshi (Kansai Univ.) NC2011-35 |
We derive a deterministic algorithm that restores and segments an image using belief propagation and a variational Bayes... [more] | NC2011-35 pp.81-86 |
| IBISML | 2011-03-28 11:30 |
Osaka | Nakanoshima Center, Osaka Univ. | MPI/OpenMP Hybrid Parallel Inference for Latent Dirichlet Allocation Shotaro Tora, Koji Eguchi (Kobe Univ.) IBISML2010-118 |
In recent years, probabilistic topic models have been applied to various kinds of data including text data, and its effe... [more] | IBISML2010-118 pp.101-108 |
| IBISML | 2010-11-04 15:00 |
Tokyo | IIS, Univ. of Tokyo | [Poster Presentation]
Image Segmentation by Region-Based Latent Variables and Belief Propagation Ryota Hasegawa, Seiji Miyoshi (Kansai Univ.), Masato Okada (Univ. of Tokyo) IBISML2010-71 |
To represent edges in image processing based on Bayesian inference, it is very effective to introduce latent variables. ... [more] | IBISML2010-71 pp.91-97 |
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