Seiichi Ozawa

According to our database, Seiichi Ozawa authored at least 107 papers between 1995 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Frameworks for Privacy-Preserving Federated Learning.

Le Trieu Phong, Tran Thi Phuong, Lihua Wang, Seiichi Ozawa

IEICE Trans. Inf. Syst., January, 2024

2023

Researcher Network Visualization Using Matrix Researcher2vec.

Enna Hirata, Takahiro Yamashita, Seiichi Ozawa

J. Adv. Comput. Intell. Intell. Informatics, July, 2023

Detecting Malicious JavaScript Using Structure-Based Analysis of Graph Representation.

Muhammad Fakhrur Rozi, Tao Ban, Seiichi Ozawa, Akira Yamada, Takeshi Takahashi, Sangwook Kim, Daisuke Inoue

IEEE Access, 2023

2022

Privacy-Preserving Federated Learning for Detecting Fraudulent Financial Transactions in Japanese Banks.

Sachiko Kanamori, Taeko Abe, Takuma Ito, Keita Emura, Lihua Wang, Shuntaro Yamamoto, Le Trieu Phong, Kaien Abe, Sangwook Kim, Ryo Nojima, Seiichi Ozawa, Shiho Moriai

J. Inf. Process., 2022

eFL-Boost: Efficient Federated Learning for Gradient Boosting Decision Trees.

Fuki Yamamoto, Seiichi Ozawa, Lihua Wang

IEEE Access, 2022

Frequency-Based Enhancement Network for Efficient Super-Resolution.

Parichehr Behjati, Pau Rodríguez, Carles Fernández Tena, Armin Mehri, F. Xavier Roca, Seiichi Ozawa, Jordi Gonzàlez

IEEE Access, 2022

Permissioned Blockchain-Based XGBoost for Multi Banks Fraud Detection.

Septiviana Savitri Asrori, Lihua Wang, Seiichi Ozawa

Proceedings of the Neural Information Processing - 29th International Conference, 2022

2021

Logo Detection With No Priors.

Diego A. Velázquez, Josep M. Gonfaus, Pau Rodríguez, F. Xavier Roca, Seiichi Ozawa, Jordi Gonzàlez

IEEE Access, 2021

Outlier Detection by Privacy-Preserving Ensemble Decision Tree U sing Homomorphic Encryption.

Kengo Itokazu, Lihua Wang, Seiichi Ozawa

Proceedings of the International Joint Conference on Neural Networks, 2021

JStrack: Enriching Malicious JavaScript Detection Based on AST Graph Analysis and Attention Mechanism.

Muhammad Fakhrur Rozi, Tao Ban, Seiichi Ozawa, Sangwook Kim, Takeshi Takahashi, Daisuke Inoue

Proceedings of the Neural Information Processing - 28th International Conference, 2021

2020

A study of IoT malware activities using association rule learning for darknet sensor data.

Seiichi Ozawa, Tao Ban, Naoki Hashimoto, Junji Nakazato, Jumpei Shimamura

Int. J. Inf. Sec., 2020

Deobfuscation, unpacking, and decoding of obfuscated malicious JavaScript for machine learning models detection performance improvement.

Samuel Ndichu, Sangwook Kim, Seiichi Ozawa

CAAI Trans. Intell. Technol., 2020

Deep Neural Networks for Malicious JavaScript Detection Using Bytecode Sequences.

Muhammad Fakhrur Rozi, Sangwook Kim, Seiichi Ozawa

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Deep Learning-based Object Detection for Crop Monitoring in Soybean Fields.

Muhammad Taufiq Pratama, Sangwook Kim, Seiichi Ozawa, Takenao Ohkawa, Yuya Chonan, Hiroyuki Tsuji, Noriyuki Murakami

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

New Approaches to Federated XGBoost Learning for Privacy-Preserving Data Analysis.

Fuki Yamamoto, Lihua Wang, Seiichi Ozawa

Proceedings of the Neural Information Processing - 27th International Conference, 2020

Port-Piece Embedding for Darknet Traffic Features and Clustering of Scan Attacks.

Shintaro Ishikawa, Seiichi Ozawa, Tao Ban

Proceedings of the Neural Information Processing - 27th International Conference, 2020

2019

Editorial: Booming of Neural Networks and Learning Systems.

Akira Hirose, Alessio Micheli, Artur S. d'Avila Garcez, Choon Ki Ahn, Gang Pan, Hamid Reza Karimi, Jianbing Shen, José de Jesús Rubio, Lei Zhang, Lingjia Liu, Lorenzo Livi, Nian Zhang, Nishchal K. Verma, Pedro Antonio Gutiérrez, Qi Tian, Qinglai Wei, Seiichi Ozawa, Stuart H. Rubin, Wei-Neng Chen, Xi Li, Xiaofeng Liao, Youmin Zhang, Zhen Ni, Haibo He

IEEE Trans. Neural Networks Learn. Syst., 2019

A machine learning approach to detection of JavaScript-based attacks using AST features and paragraph vectors.

Samuel Ndichu, Sangwook Kim, Seiichi Ozawa, Takeshi Misu, Kazuo Makishima

Appl. Soft Comput., 2019

t-Distributed Stochastic Neighbor Embedding Spectral Clustering using higher order approximations.

Nicoleta Rogovschi, Sarah Zouinina, Basarab Matei, Issam Falih, Nistor Grozavu, Seiichi Ozawa

Aust. J. Intell. Inf. Process. Syst., 2019

Exploring and Identifying Malicious Sites in Dark Web Using Machine Learning.

Yuki Kawaguchi, Seiichi Ozawa

Proceedings of the Neural Information Processing - 26th International Conference, 2019

A Fast Privacy-Preserving Multi-Layer Perceptron Using Ring-LWE-Based Homomorphic Encryption.

Takehiro Tezuka, Lihua Wang, Takuya Hayashi, Seiichi Ozawa

Proceedings of the 2019 International Conference on Data Mining Workshops, 2019

2018

Large-scale cyber attacks monitoring using Evolving Cauchy Possibilistic Clustering.

Igor Skrjanc, Seiichi Ozawa, Tao Ban, Dejan Dovzan

Appl. Soft Comput., 2018

An Image Sensing Method to Capture Soybean Growth State for Smart Agriculture Using Single Shot MultiBox Detector.

Kazuki Omura, So Yahata, Seiichi Ozawa, Takenao Ohkawa, Yuya Chonan, Hiroyuki Tsuji, Noriyuki Murakami

Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 2018

A Darknet Traffic Analysis for IoT Malwares Using Association Rule Learning.

Naoki Hashimoto, Seiichi Ozawa, Tao Ban, Junji Nakazato, Jumpei Shimamura

Proceedings of the INNS Conference on Big Data and Deep Learning 2018, 2018

A Machine Learning Approach to Malicious JavaScript Detection using Fixed Length Vector Representation.

Samuel Ndichu, Seiichi Ozawa, Takeshi Misu, Kouichirou Okada

Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

Privacy-Preserving Naive Bayes Classification Using Fully Homomorphic Encryption.

Sangwook Kim, Masahiro Omori, Takuya Hayashi, Toshiaki Omori, Lihua Wang, Seiichi Ozawa

Proceedings of the Neural Information Processing - 25th International Conference, 2018

2017

Evolving cauchy possibilistic clustering and its application to large-scale cyberattack monitoring.

Igor Skrjanc, Seiichi Ozawa, Dejan Dovzan, Tao Ban, Junji Nakazato, Jumpei Shimamura

Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

Privacy preserving extreme learning machine using additively homomorphic encryption.

Shohei Kuri, Takuya Hayashi, Toshiaki Omori, Seiichi Ozawa, Yoshinori Aono, Le Trieu Phong, Lihua Wang, Shiho Moriai

Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

A hybrid machine learning approach to automatic plant phenotyping for smart agriculture.

So Yahata, Tetsu Onishi, Kanta Yamaguchi, Seiichi Ozawa, Jun Kitazono, Takenao Ohkawa, Takeshi Yoshida, Noriyuki Murakami, Hiroyuki Tsuji

Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

t-Distributed stochastic neighbor embedding spectral clustering.

Nicoleta Rogovschi, Jun Kitazono, Nistor Grozavu, Toshiaki Omori, Seiichi Ozawa

Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

AI Web-Contents Analyzer for Monitoring Underground Marketplace.

Yuki Kawaguchi, Akira Yamada, Seiichi Ozawa

Proceedings of the Neural Information Processing - 24th International Conference, 2017

Multidimensional Unfolding Based on Stochastic Neighbor Relationship.

Naoki Murata, Jun Kitazono, Seiichi Ozawa

Proceedings of the 9th International Conference on Machine Learning and Computing, 2017

2016

Online feature extraction based on accelerated kernel principal component analysis for data stream.

Annie Anak Joseph, Takaomi Tokumoto, Seiichi Ozawa

Evol. Syst., 2016

A fast online learning algorithm of radial basis function network with locality sensitive hashing.

Siti Hajar Aminah Ali, Kiminori Fukase, Seiichi Ozawa

Evol. Syst., 2016

A sentiment polarity prediction model using transfer learning and its application to SNS flaming event detection.

Seiichi Ozawa, Shun Yoshida, Jun Kitazono, Takahiro Sugawara, Tatsuya Haga

Proceedings of the 2016 IEEE Symposium Series on Computational Intelligence, 2016

Stochastic collapsed variational Bayesian inference for biterm topic model.

Narutaka Awaya, Jun Kitazono, Toshiaki Omori, Seiichi Ozawa

Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

A neural network model for detecting DDoS attacks using darknet traffic features.

Siti Hajar Aminah Ali, Seiichi Ozawa, Tao Ban, Junji Nakazato, Jumpei Shimamura

Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

t-Distributed Stochastic Neighbor Embedding with Inhomogeneous Degrees of Freedom.

Jun Kitazono, Nistor Grozavu, Nicoleta Rogovschi, Toshiaki Omori, Seiichi Ozawa

Proceedings of the Neural Information Processing - 23rd International Conference, 2016

2015

Large-Scale Monitoring for Cyber Attacks by Using Cluster Information on Darknet Traffic Features.

Hironori Nishikaze, Seiichi Ozawa, Jun Kitazono, Tao Ban, Junji Nakazato, Jumpei Shimamura

Proceedings of the INNS Conference on Big Data 2015, 2015

An autonomous online malicious spam email detection system using extended RBF network.

Siti Hajar Aminah Ali, Seiichi Ozawa, Junji Nakazato, Tao Ban, Jumpei Shimamura

Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

Adaptive DDoS-Event Detection from Big Darknet Traffic Data.

Nobuaki Furutani, Jun Kitazono, Seiichi Ozawa, Tao Ban, Junji Nakazato, Jumpei Shimamura

Proceedings of the Neural Information Processing - 22nd International Conference, 2015

2014

Incremental two-dimensional kernel principal component analysis.

Yonghwa Choi, Seiichi Ozawa, Minho Lee

Neurocomputing, 2014

A fast Incremental Kernel Principal Component Analysis for data streams.

Annie Anak Joseph, Seiichi Ozawa

Proceedings of the 2014 International Joint Conference on Neural Networks, 2014

A Neural Network Model for Semi-supervised Sequential Multi-task Learning in Multi-label Pattern Recognition Problems.

Daisuke Higuchi, Seiichi Ozawa

Proceedings of the Smart Digital Futures 2014, 2014

Detecting Malicious Spam Mails: An Online Machine Learning Approach.

Yuli Dai, Shunsuke Tada, Tao Ban, Junji Nakazato, Jumpei Shimamura, Seiichi Ozawa

Proceedings of the Neural Information Processing - 21st International Conference, 2014

Sentiment analysis for various SNS media using Naïve Bayes classifier and its application to flaming detection.

Shun Yoshida, Jun Kitazono, Seiichi Ozawa, Takahiro Sugawara, Tatsuya Haga, Shogo Nakamura

Proceedings of the 2014 IEEE Symposium on Computational Intelligence in Big Data, 2014

Detection of DDoS Backscatter Based on Traffic Features of Darknet TCP Packets.

Nobuaki Furutani, Tao Ban, Junji Nakazato, Jumpei Shimamura, Jun Kitazono, Seiichi Ozawa

Proceedings of the Ninth Asia Joint Conference on Information Security, 2014

2013

A robust incremental principal component analysis for feature extraction from stream data with missing values.

Daijiro Aoki, Toshiaki Omori, Seiichi Ozawa

Proceedings of the 2013 International Joint Conference on Neural Networks, 2013

A Neural Network Model for Large-Scale Stream Data Learning Using Locally Sensitive Hashing.

Siti Hajar Aminah Ali, Kiminori Fukase, Seiichi Ozawa

Proceedings of the Neural Information Processing - 20th International Conference, 2013

A Neural Network Model for Online Multi-Task Multi-Label Pattern Recognition.

Daisuke Higuchi, Seiichi Ozawa

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2013, 2013

2012

Extension of Incremental Linear Discriminant Analysis to Online Feature Extraction under Nonstationary Environments.

Annie Anak Joseph, Young-Min Jang, Seiichi Ozawa, Minho Lee

Proceedings of the Neural Information Processing - 19th International Conference, 2012

A Sequential Multi-task Learning Neural Network with Metric-Based Knowledge Transfer.

Simeng Yue, Seiichi Ozawa

Proceedings of the 11th International Conference on Machine Learning and Applications, 2012

A sequential multitask learning algorithm for pattern recognition.

Tomoyasu Takata, Daisuke Higuchi, Seiichi Ozawa

Proceedings of the 2012 IEEE International Conference on Development and Learning and Epigenetic Robotics, 2012

A property of learning chunk data using incremental kernel principal component analysis.

Takaomi Tokumoto, Seiichi Ozawa

Proceedings of the 2012 IEEE Conference on Evolving and Adaptive Intelligent Systems, 2012

2011

Radial Basis Function Network for Multitask Pattern Recognition.

Hitoshi Nishikawa, Seiichi Ozawa

Neural Process. Lett., 2011

Guest editorial: Evolving autonomous systems under realistic environments.

Seiichi Ozawa, Hisashi Handa

Evol. Syst., 2011

A real-time personal authentication system based on incremental feature extraction and classification of audiovisual information.

Young-Min Jang, Minho Lee, Seiichi Ozawa

Evol. Syst., 2011

A fast incremental Kernel Principal Component Analysis for learning stream of data chunks.

Takaomi Tokumoto, Seiichi Ozawa

Proceedings of the 2011 International Joint Conference on Neural Networks, 2011

Incremental 2-directional 2-dimensional linear discriminant analysis for multitask pattern recognition.

Chunyu Liu, Young-Min Jang, Seiichi Ozawa, Minho Lee

Proceedings of the 2011 International Joint Conference on Neural Networks, 2011

A Neural Network Model for Learning Data Stream with Multiple Class Labels.

Tomoyasu Takata, Seiichi Ozawa

Proceedings of the 10th International Conference on Machine Learning and Applications and Workshops, 2011

Incremental two-dimensional two-directional principal component analysis (I(2D)²PCA) for face recognition.

Yonghwa Choi, Takaomi Tokumoto, Minho Lee, Seiichi Ozawa

Proceedings of the IEEE International Conference on Acoustics, 2011

Incremental recursive fisher linear discriminant for online feature extraction.

Seiichi Ozawa, Ryohei Ohta

Proceedings of the 2011 IEEE Workshop on Evolving and Adaptive Intelligent Systems, 2011

2010

An Autonomous Incremental Learning Algorithm for Radial Basis Function Networks.

Seiichi Ozawa, Toshihisa Tabuchi, Sho Nakasaka, Asim Roy

J. Intell. Learn. Syst. Appl., 2010

Fast Variable Selection by Block Addition and Block Deletion.

Takashi Nagatani, Seiichi Ozawa, Shigeo Abe

J. Intell. Learn. Syst. Appl., 2010

Incremental linear discriminant analysis for evolving feature spaces in multitask pattern recognition problems.

Masayuki Hisada, Seiichi Ozawa, Kau Zhang, Nikola K. Kasabov

Evol. Syst., 2010

A Fast Incremental Kernel Principal Component Analysis for Online Feature Extraction.

Seiichi Ozawa, Yohei Takeuchi, Shigeo Abe

Proceedings of the PRICAI 2010: Trends in Artificial Intelligence, 2010

A Real-Time Personal Authentication System with Selective Attention and Incremental Learning Mechanism in Feature Extraction and Classifier.

Young-Min Jang, Seiichi Ozawa, Minho Lee

Proceedings of the PRICAI 2010: Trends in Artificial Intelligence, 2010

An autonomous incremental learning algorithm of Resource Allocating Network for online pattern recognition.

Seiichi Ozawa, Sho Nakasaka, Asim Roy

Proceedings of the International Joint Conference on Neural Networks, 2010

2009

A Multitask Learning Model for Online Pattern Recognition.

Seiichi Ozawa, Asim Roy, Dmitri Roussinov

IEEE Trans. Neural Networks, 2009

Tuning membership functions of kernel fuzzy classifiers by maximizing margins.

Kazuya Morikawa, Seiichi Ozawa, Shigeo Abe

Memetic Comput., 2009

A Reinforcement Learning Model Using Macro-actions in Multi-task Grid-World Problems.

Seiichi Ozawa, Hiroshi Onda

Proceedings of the IEEE International Conference on Systems, 2009

Curiosity driven incremental LDA agent active learning.

Shaoning Pang, Seiichi Ozawa, Nikola K. Kasabov

Proceedings of the International Joint Conference on Neural Networks, 2009

Adaptive incremental principal component analysis in nonstationary online learning environments.

Seiichi Ozawa, Yuki Kawashima, Shaoning Pang, Nikola K. Kasabov

Proceedings of the International Joint Conference on Neural Networks, 2009

An incremental learning algorithm of Recursive Fisher Linear Discriminant.

Ryohei Ohta, Seiichi Ozawa

Proceedings of the International Joint Conference on Neural Networks, 2009

An Autonomous Learning Algorithm of Resource Allocating Network.

Toshihisa Tabuchi, Seiichi Ozawa, Asim Roy

Proceedings of the Intelligent Data Engineering and Automated Learning, 2009

An Incremental Learning Algorithm for Resource Allocating Networks Based on Local Linear Regression.

Seiichi Ozawa, Keisuke Okamoto

Proceedings of the Neural Information Processing, 16th International Conference, 2009

2008

Incremental Learning of Chunk Data for Online Pattern Classification Systems.

Seiichi Ozawa, Shaoning Pang, Nikola K. Kasabov

IEEE Trans. Neural Networks, 2008

Incremental Principal Component Analysis Based on Adaptive Accumulation Ratio.

Seiichi Ozawa, Kazuya Matsumoto, Shaoning Pang, Nikola K. Kasabov

Proceedings of the Advances in Neuro-Information Processing, 15th International Conference, 2008

A Neural Network Model for Sequential Multitask Pattern Recognition Problems.

Hitoshi Nishikawa, Seiichi Ozawa, Asim Roy

Proceedings of the Advances in Neuro-Information Processing, 15th International Conference, 2008

A Novel Incremental Linear Discriminant Analysis for Multitask Pattern Recognition Problems.

Masayuki Hisada, Seiichi Ozawa, Kau Zhang, Shaoning Pang, Nikola K. Kasabov

Proceedings of the Advances in Neuro-Information Processing, 15th International Conference, 2008

Incremental Learning for Multitask Pattern Recognition Problems.

Seiichi Ozawa, Asim Roy

Proceedings of the Seventh International Conference on Machine Learning and Applications, 2008

2007

A Learning Algorithm of Boosting Kernel Discriminant Analysis for Pattern Recognition.

Shinji Kita, Seiichi Ozawa, Satoshi Maekawa, Shigeo Abe

IEICE Trans. Inf. Syst., 2007

An Efficient Incremental Kernel Principal Component Analysis for Online Feature Selection.

Yohei Takeuchi, Seiichi Ozawa, Shigeo Abe

Proceedings of the International Joint Conference on Neural Networks, 2007

Adaptive Face Recognition System Using Fast Incremental Principal Component Analysis.

Seiichi Ozawa, Shaoning Pang, Nikola K. Kasabov

Proceedings of the Neural Information Processing, 14th International Conference, 2007

2006

Incremental learning of feature space and classifier for on-line pattern recognition.

Seiichi Ozawa, Shaoning Pang, Nikola K. Kasabov

Int. J. Knowl. Based Intell. Eng. Syst., 2006

An Incremental Learning Algorithm of Ensemble Classifier Systems.

Takuya Kidera, Seiichi Ozawa, Shigeo Abe

Proceedings of the International Joint Conference on Neural Networks, 2006

An Incremental Principal Component Analysis for Chunk Data.

Seiichi Ozawa, Shaoning Pang, Nikola K. Kasabov

Proceedings of the IEEE International Conference on Fuzzy Systems, 2006

2005

Incremental linear discriminant analysis for classification of data streams.

Shaoning Pang, Seiichi Ozawa, Nikola K. Kasabov

IEEE Trans. Syst. Man Cybern. Part B, 2005

Feature Extraction Using Independent Components of Each Category.

Manabu Kotani, Seiichi Ozawa

Neural Process. Lett., 2005

Incremental learning of feature space and classifier for face recognition.

Seiichi Ozawa, Soon Lee Toh, Shigeo Abe, Shaoning Pang, Nikola K. Kasabov

Neural Networks, 2005

Chunk Incremental LDA Computing on Data Streams.

Shaoning Pang, Seiichi Ozawa, Nikola K. Kasabov

Proceedings of the Advances in Neural Networks - ISNN 2005, Second International Symposium on Neural Networks, Chongqing, China, May 30, 2005

Incremental Kernel PCA for Online Learning of Feature Space.

Shosuke Kimura, Seiichi Ozawa, Shigeo Abe

Proceedings of the 2005 International Conference on Computational Intelligence for Modelling Control and Automation (CIMCA 2005), 2005

2004

Detection of gas leakage sound using modular neural networks for unknown environments.

Manabu Kotani, Masanori Katsura, Seiichi Ozawa

Neurocomputing, 2004

A Modified Incremental Principal Component Analysis for On-Line Learning of Feature Space and Classifier.

Seiichi Ozawa, Shaoning Pang, Nikola K. Kasabov

Proceedings of the PRICAI 2004: Trends in Artificial Intelligence, 2004

Supervised Independent Component Analysis with Class Information.

Manabu Kotani, Hiroki Takabatake, Seiichi Ozawa

Proceedings of the Neural Information Processing, 11th International Conference, 2004

One-Pass Incremental Membership Authentication by Face Classification.

Shaoning Pang, Seiichi Ozawa, Nikola K. Kasabov

Proceedings of the Biometric Authentication, First International Conference, 2004

A memory-based neural network model for efficient adaptation to dynamic environments.

Seiichi Ozawa, Kenji Tsumori

Proceedings of the IEEE International Conference on Fuzzy Systems, 2004

2003

Reinforcement Learning Using RBF Networks with Memory Mechanism.

Seiichi Ozawa, Naoto Shiraga

Proceedings of the Knowledge-Based Intelligent Information and Engineering Systems, 2003

2000

Training Three-Layer Neural Network Classifiers by Solving Inequalities.

Naoki Tsuchiya, Seiichi Ozawa, Shigeo Abe

Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000

1999

A Continuous-Time Model of Autoassociative Neural Memories Utilizing the Noise-Subspace Dynamics.

Seiichi Ozawa, Kazuyoshi Tsutsumi, Norio Baba

Neural Process. Lett., 1999

Evolution of a dynamical modular neural network and its application to associative memories.

Seiichi Ozawa, K. Tsutumi, Norio Baba

Proceedings of the Third International Conference on Knowledge-Based Intelligent Information Engineering Systems, 1999

Emergence of feature extraction function using genetic programming.

Manabu Kotani, Seiichi Ozawa, Masaki Nakai, Kenzo Akazawa

Proceedings of the Third International Conference on Knowledge-Based Intelligent Information Engineering Systems, 1999

Application of independent component analysis to handwritten Japanese character recognition.

Seiichi Ozawa, Toshihide Tsujimoto, Manabu Kotani, Norio Baba

Proceedings of the International Joint Conference Neural Networks, 1999

Application of independent component analysis to feature extraction of speech.

Manabu Kotani, Yasunobu Shirata, Satoshi Maekawa, Seiichi Ozawa, Kenzo Akazawa

Proceedings of the International Joint Conference Neural Networks, 1999

1998

An artificial modular neural network and its basic dynamical characteristics.

Seiichi Ozawa, Kazuyoshi Tsutsumi, Norio Baba

Biol. Cybern., 1998

Design of Modular Neural Network Architectures Using Genetic Algorithms.

Seiichi Ozawa, Kazuyoshi Tsutsumi, Norio Baba

Proceedings of the Fifth International Conference on Neural Information Processing, 1998

1995

A multimodule neural network model and the estimate of its nature as associative memory.

Seiichi Ozawa, Kazuyoshi Tsutsumi

Syst. Comput. Jpn., 1995