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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| PRMU, IBISML, IPSJ-CVIM | 2024-03-03 09:36 |
Hiroshima | Hiroshima Univ. Higashi-Hiroshima campus (Primary: On-site, Secondary: Online) |
Sign language recognition using subspace representations Ryota Sato, Suzana Rita Alves Beleza (Univ. of Tsukuba), Erica Kido Shimomoto (AIST), Matheus Silva de Lima (Univ. of Tsukuba), Nobuko Kato (Tsukuba Univ. of Technology), Kazuhiro Fukui (Univ. of Tsukuba)  PRMU2023-54 |
This paper proposes a subspace-based method for sign language recognition in videos. The proposed method represents a ... [more] |
PRMU2023-54 pp.19-24 |
| SIP | 2023-08-07 14:45 |
Osaka | Osaka Univ. (Suita) Convention Center (Primary: On-site, Secondary: Online) |
[Invited Talk]
On optimization over Stiefel manifold based on adaptive Cayley parametrization Keita Kume, Isao Yamada (TokyoTech) SIP2023-50 |
The Stiefel manifold, say St(p,N), is the set of all N-by-p matrices whose column vectors are orthonormal. Optimization ... [more] | SIP2023-50 p.20 |
| PRMU, IBISML, IPSJ-CVIM [detail] | 2023-03-02 11:40 |
Hokkaido | Future University Hakodate (Primary: On-site, Secondary: Online) |
Novel Adversarial Attacks Based on Embedding Geometry of Data Manifolds Masahiro Morita, Hajime Tasaki, Jinhui Chao (Chuo Univ.) PRMU2022-84 IBISML2022-91 |
It has been shown recently that adversarial examples inducing misclassification by deep neural networks exist in the ort... [more] | PRMU2022-84 IBISML2022-91 pp.140-145 |
| SP, IPSJ-SLP, EA, SIP [detail] | 2023-03-01 15:50 |
Okinawa | (Primary: On-site, Secondary: Online) |
Multiscale Manifold Clustering and Embedding with Multiple Kernels Kyohei Suzuki, Masahiro Yukawa (Keio Univ.) EA2022-123 SIP2022-167 SP2022-87 |
This paper presents a clustering and embedding method to analyze data which lie on a union of multiple manifolds having ... [more] | EA2022-123 SIP2022-167 SP2022-87 pp.276-281 |
| SIP | 2022-08-26 15:51 |
Okinawa | Nobumoto Ohama Memorial Hall (Ishigaki Island) (Primary: On-site, Secondary: Online) |
Design of Structured Convolutional Dictionary by Manifold Optimization for Image Restoration Soushi Takahashi, Shogo Muramatsu (Niigata Univ.) SIP2022-76 |
This work reports on the effectiveness of a structured convolutional dictionary learning that introduces manifold optimi... [more] | SIP2022-76 pp.134-139 |
| EA, SIP, SP, IPSJ-SLP [detail] | 2022-03-02 15:35 |
Okinawa | (Primary: On-site, Secondary: Online) |
[Poster Presentation]
Epileptic Seizure Detection Using Active Learning with Riemannian Manifold Toshiki Orihara, Toshihisa Tanaka (TUAT) EA2021-96 SIP2021-123 SP2021-81 |
In order to realize machine learning for diagnosis, it is necessary to solve the problem that the training model is not ... [more] | EA2021-96 SIP2021-123 SP2021-81 pp.201-206 |
| PRMU | 2021-10-09 09:30 |
Online | Online | Explaining Adversarial Examples by the Embedding Structure of Data Manifold Hajime Tasaki, Yuji Kaneko, Jinhui Chao (Chuo Univ.) PRMU2021-19 |
It is widely known that adversarial examples cause misclassification in classifiers using deep learning. Inspite of nume... [more] | PRMU2021-19 pp.17-21 |
| PRMU, MI, IPSJ-CVIM [detail] | 2019-09-05 14:10 |
Okayama | Analysis and Feature Selection of CNN Features
-- Recognition of Neoplasia by using Endocytoscopic Images -- Hayato Itoh (Nagoya Univ.), Yuichi Mori, Masashi Misawa (Showa Univ.), Masahiro Oda (Nagoya Univ.), Shin-Ei Kudo (Showa Univ.), Kensaku Mori (Nagoya Univ.) PRMU2019-29 MI2019-48 |
Pathological pattern classification is based on texture patterns in ultra magnified view of polyp surfaces. Deep learni... [more] |
PRMU2019-29 MI2019-48 pp.129-134 |
|
| MI | 2019-01-23 09:45 |
Okinawa | Feature Selection from Imbalanced Data
-- Pathological Pattern Classification in Endocytoscopic Images -- Hayato Itoh (Nagoya Univ.), Yuichi Mori, Masashi Misawa (Showa Univ.), Masahiro Oda (Nagoya Univ.), Shin-Ei Kudo (Showa Univ.), Kensaku Mori (Nagoya Univ.) MI2018-87 |
Endocytoscope gives ultramagnified observation that enables physicians to achieve minimally invasive and real-time diagn... [more] | MI2018-87 pp.109-114 |
|
| SIP, EA, SP, MI (Joint) [detail] |
2018-03-19 15:25 |
Okinawa | Feature-selection method based on Grassmann distance for the classification of neoplastic polyps on endocytoscopic images Hayato Itoh (Nagoya Univ.), Yuichi Mori, Masashi Misawa (Showa Univ.), Masahiro Oda (Nagoya Univ.), Shin-ei Kudo (Showa Univ.), Kensaku Mori (Nagoya Univ.) MI2017-81 |
An endocytoscope provides ultramagnified observation that enable physicians to achieve minimally invasive and real-time ... [more] | MI2017-81 pp.51-56 |
|
| MBE, NC (Joint) |
2017-11-24 16:50 |
Miyagi | Tohoku University | NC2017-32 |
Continuous latent variable model is a category of dimension reduction methods, which estimates low dimensional latent va... [more] | NC2017-32 pp.29-34 |
| PRMU, BioX | 2017-03-20 10:50 |
Aichi | Structure Estimation of Topological Manifolds and Manifold Learning Hajime Tasaki (Chuo Univ.), Reiner Lenz (Linkoping Univ.), Jinhui Chao (Chuo Univ.) BioX2016-35 PRMU2016-198 |
Manifold learning algorithms try to find the low dimensional representation of high dimensional data for the visualizati... [more] | BioX2016-35 PRMU2016-198 pp.11-15 |
|
| IBISML | 2016-11-17 14:00 |
Kyoto | Kyoto Univ. | [Poster Presentation]
Analysis of Multimodal Deep Neural Networks
-- Towards the elucidation of the modality integration mechanism -- Yoh-ichi Mototake, Takashi Ikegami (unit of Tokyo) IBISML2016-97 |
With the rapid development of information technology in recent years, several machine learning algorithms that integra... [more] |
IBISML2016-97 pp.369-373 |
| PRMU, SP, WIT, ASJ-H | 2016-06-13 11:15 |
Tokyo | Preliminary study on deep manifold embedding for 3D object pose estimation Hiroshi Ninomiya, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase (Nagoya Univ.), Norimasa Kobori, Kunimatsu Hashimoto (Toyota) PRMU2016-39 SP2016-5 WIT2016-5 |
Recently, 3D object pose estimation is being focused. The parametric eigenspace method is known as one of the fundamenta... [more] | PRMU2016-39 SP2016-5 WIT2016-5 pp.25-30 |
|
| IBISML | 2016-03-18 11:30 |
Tokyo | Institute of Statistical Mathematics | Dimension Estimation of Topological Manifolds based on Measure of Simplexes and Application to Manifold Learning Hajime Tasaki, Jinhui Chao (Chuo Univ.) IBISML2015-102 |
Dimension reduction is one of the most important issues in machine learning and computational intelligence for reduction... [more] | IBISML2015-102 pp.59-62 |
| NLP | 2015-11-01 14:30 |
Okinawa | Nobumoto Ohama Memorial Hall | The hierarchical visualizing and learning method in the generative topographic mapping Takehito Oshita (BCI), Mikio Hasegawa (Tokyo Univ. of Science) NLP2015-124 |
Generative Topographic Mapping(GTM) is the latent variable model which is formalized Kohonen’s Self-Organization Map in ... [more] | NLP2015-124 pp.99-103 |
| MI | 2014-01-26 13:30 |
Okinawa | Bunka Tenbusu Kan | Newborn brain growth model using manifold learning Ryosuke Nakano (Univ. of Hyogo), Syoji Kobashi, Kei Kuramoto (Univ. of Hyogo/WPI-IFReC), Yuki Wakata, Kumiko Ando, Reiichi Ishikura (Hyogo College of Medicine), Tomomoto Ishikawa (Ishikawa Hospital), Shozo Hirota (Hyogo College of Medicine), Yutaka Hata (Univ. of Hyogo/Osaka Univ.) MI2013-64 |
To develop a computer-aided diagnosis system for neonatal cerebral disorders, some literatures have shown atlas-based me... [more] | MI2013-64 pp.47-52 |
| NC | 2012-10-04 17:20 |
Fukuoka | Kyushu Institute of Technology (Wakamatsu Campus) | Improvement of Gesture Recognition based on Higher-rank Self-Organizing Map with Graph-based Distance Norihiro Fujita, Keiichi Horio (Kyushu Inst. of Tech.) NC2012-47 |
The authors proposed a gesture recognition method which is based on higher-rank self-organizing map. In the method, a ge... [more] | NC2012-47 pp.61-66 |
| NC | 2012-07-30 10:20 |
Shiga | Ritsumeikan Univ. College of Information Science and Engineering | Neuroevolution with Manifold Learning for Mario AI Hisashi Handa (Kinki Univ.) NC2012-13 |
This talk presents a Neuroevolution with Manifold Learning for Mario AI championship. The Manifold Learning method provi... [more] | NC2012-13 pp.1-4 |
| PRMU, MI, IE | 2012-05-17 10:30 |
Aichi | Image Super-Resolution using Manifold Learning with Vector Quantization Kazuki Taniguchi, Xian-Hua Han, Yutaro Iwamoto, So Sasatani, Yen-Wei Chen (Ritsumeikan Univ.) IE2012-19 PRMU2012-4 MI2012-4 |
Image Super-Resolution (SR) is to recover the lost high-frequency information from several or only one available image. ... [more] | IE2012-19 PRMU2012-4 MI2012-4 pp.19-24 |
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