| IEICE Technical Committee Submission System Conference Schedule |
Online Proceedings [Sign in] Tech. Rep. Archives |
All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| 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 |
|
| NC | 2012-01-26 15:15 |
Hokkaido | Future University Hakodate | The learning theory and algorithm of latent multi-dynamical systems
-- Implementation by higher-order topographic mapping -- Tetsuo Furukawa, Takashi Ohkubo (Kyutech) NC2011-107 |
The purpose of this paper is to establish the learning theory of multiple dynamical systems, as well as to develop the ... [more] |
NC2011-107 pp.59-64 |
| NLP | 2011-03-10 14:20 |
Tokyo | Tokyo University of Science | A Manifold Learning Approach for Analyzing Chaos in A Dripping Faucet System Hiromichi Suetani (Kagoshima Univ./JST/RIKEN), Hiroki Kuroiwa, Hiroki Hata (Kagoshima Univ.), Shotaro Akaho (AIST) NLP2010-173 |
Dripping water from a faucet is very familiar to us and it provides various nonlinear phenomena including chaos. When i... [more] | NLP2010-173 pp.57-62 |
[Return to Top Page]