Seiichi Ozawa

发表

Emergence of feature extraction function using genetic programming

Manabu Kotani, Seiichi Ozawa, M. Nakai, 1999, 1999 Third International Conference on Knowledge-Based Intelligent Information Engineering Systems. Proceedings (Cat. No.99TH8410).

Feature Extraction Using Independent Components of Each Category

Manabu Kotani, Seiichi Ozawa, S. Ozawa, 2005, Neural Processing Letters.

A Fast Incremental Learning Algorithm for Radial Basis Function Networks

Shigeo Abe, Seiichi Ozawa, Keisuke Okamoto, 2004 .

An incremental learning algorithm of Recursive Fisher Linear Discriminant

Seiichi Ozawa, Ryohei Ohta, 2009, 2009 International Joint Conference on Neural Networks.

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

Seiichi Ozawa, Takaomi Tokumoto, 2011, The 2011 International Joint Conference on Neural Networks.

A Reinforcement Learning Model with Function of Generating Macro-Actions in Grid-World Maze Problems and a Study on its Learning Property

Seiichi Ozawa, Hiroshi Onda, 2009 .

The estimation of cross-coupled Hopfield nets as an interactive modular neural network

Kazuyoshi Tsutsumi, Norio Baba, Seiichi Ozawa, 1994, Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94).

Incremental linear discriminant analysis for classification of data streams

Shaoning Pang, Nikola K. Kasabov, Seiichi Ozawa, 2005, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

Basic dynamical properties of cross-coupled Hopfield nets

Kazuyoshi Tsutsumi, Seiichi Ozawa, Haruya Matsumoto, 1991, [Proceedings] 1991 IEEE International Joint Conference on Neural Networks.

Privacy preserving extreme learning machine using additively homomorphic encryption

Shiho Moriai, Seiichi Ozawa, Yoshinori Aono, 2017, 2017 IEEE Symposium Series on Computational Intelligence (SSCI).

Adaptive DDoS-Event Detection from Big Darknet Traffic Data

Tao Ban, Seiichi Ozawa, Jumpei Shimamura, 2015, ICONIP.

Large-scale cyber attacks monitoring using Evolving Cauchy Possibilistic Clustering

Dejan Dovzan, Igor Skrjanc, Tao Ban, 2018, Appl. Soft Comput..

A reinforcement learning algorithm for neural networks with incremental learning ability

Shigeo Abe, Seiichi Ozawa, Naoto Shiraga, 2002, Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02..

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

Seiichi Ozawa, Toshiaki Omori, Daijiro Aoki, 2013, The 2013 International Joint Conference on Neural Networks (IJCNN).

Stochastic collapsed variational Bayesian inference for biterm topic model

Seiichi Ozawa, Toshiaki Omori, Jun Kitazono, 2016, 2016 International Joint Conference on Neural Networks (IJCNN).

Multidimensional Unfolding Based on Stochastic Neighbor Relationship

Seiichi Ozawa, Naoki Murata, Jun Kitazono, 2017, ICMLC.

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

Seiichi Ozawa, Jun Kitazono, Shun Yoshida, 2016, 2016 IEEE Symposium Series on Computational Intelligence (SSCI).

The CV Syllable Recognition Using Multi-Layered Kohonen Net

Kazuyoshi Tsutsumi, Seiichi Ozawa, Haruya Matsumoto, 1989 .

Incremental learning in dynamic environments using neural network with long-term memory

Seiichi Ozawa, K. Tsumori, 2003, Proceedings of the International Joint Conference on Neural Networks, 2003..

An Efficient Incremental KernelPrincipal ComponentAnalysis forOnlineFeature Selection

Shigeo Abe, Seiichi Ozawa, 2007 .

Neural Information Processing

Seiichi Ozawa, Long Cheng, Andrew Chi Sing Leung, 2018, Lecture Notes in Computer Science.

A fast incremental learning algorithm of RBF networks with long-term memory

Shigeo Abe, Seiichi Ozawa, K. Okamato, 2003, Proceedings of the International Joint Conference on Neural Networks, 2003..

Signal Processing of Speech Using Independent Component Analysis Based on Information Maximization Algorithm

Manabu Kotani, Seiichi Ozawa, Kenzo Akazawa, 2000 .

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

Seiichi Ozawa, Takuya Hayashi, Lihua Wang, 2019, 2019 International Conference on Data Mining Workshops (ICDMW).

Neural Information Processing

Akira Hirose, Minho Lee, Derong Liu, 2016, Lecture Notes in Computer Science.

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

Seiichi Ozawa, Basarab Matei, Nicoleta Rogovschi, 2019, Aust. J. Intell. Inf. Process. Syst..

An Incremental Principal Component Analysis for Chunk Data

Shaoning Pang, Nikola K. Kasabov, Seiichi Ozawa, 2006, 2006 IEEE International Conference on Fuzzy Systems.

Incremental Learning Algorithm for Feedforward Neural Network with Long-Term Memory

Shigeo Abe, Seiichi Ozawa, Masataka Kobayashi, 2002 .

Fast Online Feature Extraction Using Chunk Incremental Kernel Principal Component Analysis

Seiichi Ozawa, Annie anak Joseph, 2014 .

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

Kazuyoshi Tsutsumi, Seiichi Ozawa, 1995, Systems and Computers in Japan.

Acoustic Diagnosis with Modular Neural Networks to Adapt Dynamic Environment

Manabu Kotani, Seiichi Ozawa, Kenzo Akazawa, 2000 .

Incremental learning of feature space and classifier for face recognition

Shigeo Abe, Shaoning Pang, Nikola K. Kasabov, 2005, Neural Networks.

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

Seiichi Ozawa, Lihua Wang, Fuki Yamamoto, 2020, ICONIP.

A fast Incremental Kernel Principal Component Analysis for data streams

Seiichi Ozawa, Annie Anak Joseph, 2014, 2014 International Joint Conference on Neural Networks (IJCNN).

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

Tao Ban, Seiichi Ozawa, Shintaro Ishikawa, 2020, ICONIP.

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

Tao Ban, Seiichi Ozawa, Siti Hajar Aminah Ali, 2015, 2015 International Joint Conference on Neural Networks (IJCNN).

Neural Information Processing

Akira Hirose, Kazushi Ikeda, Kenji Doya, 2014, Lecture Notes in Computer Science.

Neural Information Processing

Akira Hirose, Minho Lee, Derong Liu, 2016, Lecture Notes in Computer Science.

Feature extraction using supervised independent component analysis by maximizing class distance

Manabu Kotani, Seiichi Ozawa, Y. Sakaguchi, 2002, Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02..

Supervised Independent Component Analysis with Class Information

Manabu Kotani, Seiichi Ozawa, Hiroki Takabatake, 2004, ICONIP.

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

Seiichi Ozawa, Takaomi Tokumoto, 2012, 2012 IEEE Conference on Evolving and Adaptive Intelligent Systems.

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

Minho Lee, Seiichi Ozawa, Yonghwa Choi, 2011, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

A Fast Incremental Learning Algorithm for Feed-forward Neural Networks Using Resilient Propagation

Seiichi Ozawa, Annie anak Joseph, 2014 .

Reinforcement Learning Using RBF Networks with Memory Mechanism

Seiichi Ozawa, Naoto Shiraga, 2003, KES.

Feature extraction by supervised independent component analysis based on category information

Manabu Kotani, Seiichi Ozawa, Hiroki Takabatake, 2007 .

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

Hiroyuki Tsuji, Takeshi Yoshida, Takenao Ohkawa, 2017, 2017 International Joint Conference on Neural Networks (IJCNN).

Neural Information Processing

Akira Hirose, Minho Lee, Derong Liu, 2016, Lecture Notes in Computer Science.

A Memory-Based Reinforcement Learning Algorithm to Prevent Unlearning in Neural Networks

Shigeo Abe, Seiichi Ozawa, 2004 .

Online Incremental Face Recognition System Using Eigenface Feature and Neural Classifier

Shigeo Abe, Nikola Kasabov, Shaoning Pang, 2009 .

Application of independent component analysis to detection of gas leakage sound

Manabu Kotani, Kenzo Akazawa, Seiichi Ozawa, 2001, IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222).

Feature extraction by supervised independent component analysis based on category information

Manabu Kotani, Seiichi Ozawa, Hiroki Takabatake, 2007 .

Training three-layer neural network classifiers by solving inequalities

Naoki Tsuchiya, Shigeo Abe, Seiichi Ozawa, 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

A Memory-Based Reinforcement Learning Model Utilizing Macro-Actions

Seiichi Ozawa, Makoto Murata, 2005 .

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

Tao Ban, Seiichi Ozawa, Siti Hajar Aminah Ali, 2016, 2016 International Joint Conference on Neural Networks (IJCNN).

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

Minho Lee, Seiichi Ozawa, Young-Min Jang, 2012, ICONIP.

Distributed Denial of Service (DDoS) Backscatter Detection System Using Resource Allocating Network with Data Selection

Tao Ban, Seiichi Ozawa, Jumpei Shimamura, 2015 .

Performance Improvement fo Dynamical Associative Memories by Solving Linear Inequalities

Shigeo Abe, Seiichi Ozawa, Jungpil Park, 2001 .

Incremental LearningforOnlineFace Recognition

Seiichi Ozawa, Shaoning PangandNikola Kasabov, 2005 .

A Darknet Traffic Analysis for IoT Malwares Using Association Rule Learning

Naoki Hashimoto, Tao Ban, Seiichi Ozawa, 2018, INNS Conference on Big Data.

Online Feature Extraction Algorithms for Data Streams: —Incremental Principal Component Analysis—@@@—追加型主成分分析—

Seiichi Ozawa, 2012 .

Fast Variable Selection by Block Addition and Block Deletion

Shigeo Abe, Takashi Nagatani, Seiichi Ozawa, 2010, J. Intell. Learn. Syst. Appl..

Incremental recursive fisher linear discriminant for online feature extraction

Seiichi Ozawa, Ryohei Ohta, S. Ozawa, 2011, 2011 IEEE Workshop on Evolving and Adaptive Intelligent Systems (EAIS).

Radial Basis Function Network for Multitask Pattern Recognition

Seiichi Ozawa, Hitoshi Nishikawa, 2011, Neural Processing Letters.

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

Seiichi Ozawa, Tomoyasu Takata, 2011, 2011 10th International Conference on Machine Learning and Applications and Workshops.

An Incremental Linear Discriminant Analysis for Data Streams Under Non-stationary Environments (SCI'13論文特集号(3))

Seiichi Ozawa, Young-Min Jang, Annie anak Joseph, 2014 .

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

Seiichi Ozawa, Takaomi Tokumoto, Annie Anak Joseph, 2015, Evolving Systems.

Tuning membership functions of kernel fuzzy classifiers by maximizing margins

Shigeo Abe, Seiichi Ozawa, Kazuya Morikawa, 2009, Memetic Comput..

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

Dejan Dovzan, Igor Skrjanc, Tao Ban, 2017, 2017 IEEE Symposium Series on Computational Intelligence (SSCI).

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

Minho Lee, Seiichi Ozawa, Young-Min Jang, 2011, The 2011 International Joint Conference on Neural Networks.

Neural Network Approaches to Robot Control

Norio Baba, Seiichi Ozawa, 1993 .

Editorial: Booming of Neural Networks and Learning Systems

Akira Hirose, Pedro Antonio Gutiérrez, Haibo He, 2019, IEEE Trans. Neural Networks Learn. Syst..

A sequential multitask learning algorithm for pattern recognition

Seiichi Ozawa, Tomoyasu Takata, Daisuke Higuchi, 2012, 2012 IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL).

Exploring and Identifying Malicious Sites in Dark Web Using Machine Learning

Seiichi Ozawa, Yuki Kawaguchi, 2019, ICONIP.

Incremental Principal Component Analysis Based on Adaptive Accumulation Ratio

Shaoning Pang, Nikola K. Kasabov, Seiichi Ozawa, 2008, ICONIP.

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

Hiroyuki Tsuji, Takenao Ohkawa, Seiichi Ozawa, 2018, 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

An Incremental Learning Algorithm of Ensemble Classifier Systems

Shigeo Abe, Seiichi Ozawa, Takuya Kidera, 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

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

Minho Lee, Seiichi Ozawa, Young-Min Jang, 2011, Evol. Syst..

Feature Extraction of Digit Patterns Utilizing Independent Component Analysis

Manabu Kotani, Seiichi Ozawa, S. Ozawa, 2002 .

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

Seiichi Ozawa, Shogo Nakamura, Jun Kitazono, 2014, 2014 IEEE Symposium on Computational Intelligence in Big Data (CIBD).

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

Naoki Hashimoto, Tao Ban, Seiichi Ozawa, 2019, International Journal of Information Security.

Optimal Pattern Mining from Time-Series Cultivation Data of Soybeans for Knowledge Discovery

Hiroyuki Tsuji, Seiichi Ozawa, Noriyuki Murakami, 2016, TSAA '16.

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

Kazuyoshi Tsutsumi, Norio Baba, Seiichi Ozawa, 2004, Neural Processing Letters.

2014 IEEE Symposium on Computational Intelligence in Big Data, CIBD 2014, Orlando, FL, USA, December 9-12, 2014

Xiaodong Li, Jian Wang, Baoyan Liu, 2014, CIBD.

Personality Trait Analysis in Social Networks Based on Weakly Supervised Learning of Shared Images

Jordi Gonzàlez, Seiichi Ozawa, Pau Rodríguez, 2020, Applied Sciences.

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

Hiroyuki Tsuji, Takenao Ohkawa, Seiichi Ozawa, 2020, 2020 International Joint Conference on Neural Networks (IJCNN).

Neural Information Processing

Seiichi Ozawa, Long Cheng, Andrew Chi Sing Leung, 2018, Lecture Notes in Computer Science.

Incremental Learning of Chunk Data for Online Pattern Classification Systems

Shaoning Pang, Nikola K. Kasabov, Seiichi Ozawa, 2008, IEEE Transactions on Neural Networks.

Neural Information Processing

Seiichi Ozawa, Long Cheng, Andrew Chi Sing Leung, 2018, Lecture Notes in Computer Science.

40.3: A 2Gbps/lane Source Synchronous Intra‐Panel Interface for Large Size and High Refresh Rate Panel with Automatic Calibration

Shogo Hachiya, Seiichi Ozawa, Hidetoshi Miura, 2011 .

Incremental Kernel PCA for Online Learning of Feature Space

Shigeo Abe, Seiichi Ozawa, Shosuke Kimura, 2005, International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce (CIMCA-IAWTIC'06).

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

Seiichi Ozawa, Siti Hajar Aminah Ali, Kiminori Fukase, 2016, Evol. Syst..

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

Tao Ban, Seiichi Ozawa, Jumpei Shimamura, 2015, INNS Conference on Big Data.

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

Shaoning Pang, Nikola K. Kasabov, Seiichi Ozawa, 2004, PRICAI.

Improving the Accuracy of Sentiment Analysis of SNS Comments Using Transfer Learning and Its Application to Flaming Detection

Seiichi Ozawa, Jun Kitazono, Shun Yoshida, 2016 .

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

Seiichi Ozawa, Siti Hajar Aminah Ali, Kiminori Fukase, 2013, ICONIP.

t-Distributed stochastic neighbor embedding spectral clustering

Seiichi Ozawa, Toshiaki Omori, Nicoleta Rogovschi, 2017, 2017 International Joint Conference on Neural Networks (IJCNN).

An Online Malicious Spam Email Detection System Using Resource Allocating Network with Locality Sensitive Hashing

Tao Ban, Seiichi Ozawa, Jumpei Shimamura, 2015 .

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

Seiichi Ozawa, Keisuke Okamoto, 2009, ICONIP.

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

Seiichi Ozawa, Samuel Ndichu, Takeshi Misu, 2018, 2018 International Joint Conference on Neural Networks (IJCNN).

Analysis of DNA microarray data using self-organizing map and kernel based clustering

Manabu Kotani, Seiichi Ozawa, A. Sugiyama, 2002, Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02..

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

Seiichi Ozawa, Simeng Yue, S. Ozawa, 2012, 2012 11th International Conference on Machine Learning and Applications.

An Autonomous Incremental Learning Algorithm for Radial Basis Function Networks

Seiichi Ozawa, Asim Roy, Toshihisa Tabuchi, 2010, J. Intell. Learn. Syst. Appl..

A Neural Network Model for Incremental Learning of Large-Scale Stream Data

Seiichi Ozawa, Kiminori Fukase, Ali Siti Hajar Aminah, 2014 .

A Learning Algorithm of Boosting Kernel Discriminant Analysis for Pattern Recognition

Shigeo Abe, Seiichi Ozawa, Satoshi Maekawa, 2007, IEICE Trans. Inf. Syst..

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

Seiichi Ozawa, Samuel Ndichu, Sangwook Kim, 2020, CAAI Trans. Intell. Technol..

A Fast Incremental Kernel Principal Component Analysis for Online Feature Extraction

Shigeo Abe, Seiichi Ozawa, Yohei Takeuchi, 2010, PRICAI.

Pattern Recognition Method Using Independent Components for Each Class

Manabu Kotani, Seiichi Ozawa, Shuhei Kinukawa, 2005 .

An Associative Memory ModelI Derived from Cross-Coupled Hopfield Nets and The Roll of Noise-Space Dynamics

Kazuyoshi Tsutsumi, Norio Baba, Seiichi Ozawa, 1997 .

Application of independent component analysis to feature extraction of speech

Manabu Kotani, Seiichi Ozawa, Kenzo Akazawa, 1999, IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339).

Study on Detection of Leakage Sound Using Independent Component Analysis

Manabu Kotani, Seiichi Ozawa, Takahiko Arimoto, 2003 .

Guest editorial: Evolving autonomous systems under realistic environments

Seiichi Ozawa, Hisashi Handa, 2011, Evol. Syst..

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

Shaoning Pang, Nikola K. Kasabov, Seiichi Ozawa, 2006, Int. J. Knowl. Based Intell. Eng. Syst..

A Fast Incremental Learning for Radial Basis Function Networks Using Local Linear Regression

Seiichi Ozawa, Keisuke Okamoto, S. Ozawa, 2010 .

Deep Neural Networks for Malicious JavaScript Detection Using Bytecode Sequences

Seiichi Ozawa, Sangwook Kim, Muhammad Fakhrur Rozi, 2020, 2020 International Joint Conference on Neural Networks (IJCNN).

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

Seiichi Ozawa, Kenji Tsumori, 2004, 2004 IEEE International Conference on Fuzzy Systems (IEEE Cat. No.04CH37542).

A study of feature extraction using supervised independent component analysis

Manabu Kotani, Seiichi Ozawa, Y. Sakaguchi, 2001, IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222).

Adaptive incremental principal component analysis in nonstationary online learning environments

Shaoning Pang, Nikola K. Kasabov, Seiichi Ozawa, 2009, 2009 International Joint Conference on Neural Networks.

Reinforcement Learning Using Feedforward Neural Network with Memory Mechanism

Seiichi Ozawa, Naoto Shiraga, 2003 .

An Efficient Incremental Kernel Principal Component Analysis for Online Feature Selection

Shigeo Abe, Seiichi Ozawa, Yohei Takeuchi, 2007, 2007 International Joint Conference on Neural Networks.

A Neural Network Model for Sequential Multitask Pattern Recognition Problems

Seiichi Ozawa, Asim Roy, Hitoshi Nishikawa, 2008, ICONIP.

Reducing computations in incremental learning for feedforward neural network with long-term memory

Shigeo Abe, Seiichi Ozawa, M. Kobyashi, 2001, IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222).

AI Web-Contents Analyzer for Monitoring Underground Marketplace

Akira Yamada, Seiichi Ozawa, Yuki Kawaguchi, 2017, ICONIP.

Boosting Kernel Discriminant Analysis with Adaptive Kernel Selection

Shigeo Abe, Seiichi Ozawa, Satoshi Maekawa, 2005 .

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

Norio Baba, Seiichi Ozawa, K. Tsutumi, 1999, 1999 Third International Conference on Knowledge-Based Intelligent Information Engineering Systems. Proceedings (Cat. No.99TH8410).

An Autoassociative Memory Model Derived from a Modular Neural Network and a Diversity of the Association Properties

Kazuyoshi Tsutsumi, Norio Baba, Seiichi Ozawa, 1997 .

Incremental Learning for Multitask Pattern Recognition Problems

Seiichi Ozawa, Asim Roy, 2008, 2008 Seventh International Conference on Machine Learning and Applications.

Incremental two-dimensional kernel principal component analysis

Minho Lee, Seiichi Ozawa, Yonghwa Choi, 2014, Neurocomputing.

Handling Concept Drift Using Incremental Linear Discriminant Analysis with Knowledge Transfer in Non-stationary Data Streams

Seiichi Ozawa, Annie anak Joseph, 2013 .

Privacy-Preserving Naive Bayes Classification Using Fully Homomorphic Encryption

Sangwook Kim, Seiichi Ozawa, Toshiaki Omori, 2018, ICONIP.

2012 IEEE Conference on Evolving and Adaptive Intelligent Systems, EAIS 2012, Madrid, Spain, May 17-18, 2012

Seiichi Ozawa, Takaomi Tokumoto, Ichiro Satoh, 2012, EAIS.

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

Seiichi Ozawa, Samuel Ndichu, Kazuo Makishima, 2019, Appl. Soft Comput..

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

Seiichi Ozawa, Asim Roy, Sho Nakasaka, 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

Association performance of cross-coupled Hopfield nets for correlated patterns

Kazuyoshi Tsutsumi, Seiichi Ozawa, S. Ozawa, 1993, Proceedings of 1993 International Conference on Neural Networks (IJCNN-93-Nagoya, Japan).

Computational Intelligence in the Time of Cyber-Physical Systems and the Internet of Things

Cesare Alippi, Seiichi Ozawa, S. Ozawa, 2019, Artificial Intelligence in the Age of Neural Networks and Brain Computing.

t-Distributed Stochastic Neighbor Embedding with Inhomogeneous Degrees of Freedom

Seiichi Ozawa, Toshiaki Omori, Nicoleta Rogovschi, 2016, ICONIP.

Design of Modular Neural Network Architectures Using Genetic Algorithms

Kazuyoshi Tsutsumi, Norio Baba, Seiichi Ozawa, 1998, ICONIP.

A reinforcement learning algorithm for a class of dynamical environments using neural networks

Seiichi Ozawa, M. Murata, 2003, SICE 2003 Annual Conference (IEEE Cat. No.03TH8734).

An Architecture Design Method of Modular Dynamical Neural Networks Using Genetic Algorithms

Kazuyoshi Tsutsumi, Norio Baba, Seiichi Ozawa, 2000 .

A reinforcement learning model using macro-actions in multi-task grid-world problems

Seiichi Ozawa, Hiroshi Onda, 2009, 2009 IEEE International Conference on Systems, Man and Cybernetics.

Neural Information Processing

Seiichi Ozawa, Long Cheng, Andrew Chi Sing Leung, 2018, Lecture Notes in Computer Science.

Correction to: Neural Information Processing

Seiichi Ozawa, Long Cheng, Andrew Chi Sing Leung, 2018, ICONIP 2018.

Adaptive Face Recognition System Using Fast Incremental Principal Component Analysis

Shaoning Pang, Nikola K. Kasabov, Seiichi Ozawa, 2007, ICONIP.

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

Seiichi Ozawa, Daisuke Higuchi, 2014, IDT/IIMSS/STET.

Chunk Incremental LDA Computing on Data Streams

Shaoning Pang, Nikola K. Kasabov, Seiichi Ozawa, 2005, ISNN.

An Autonomous Learning Algorithm of Resource Allocating Network

Seiichi Ozawa, Asim Roy, Toshihisa Tabuchi, 2009, IDEAL.

An artificial modular neural network and its basic dynamical characteristics

Kazuyoshi Tsutsumi, Norio Baba, Seiichi Ozawa, 1998, Biological Cybernetics.

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

Minho Lee, Seiichi Ozawa, Young-Min Jang, 2010, PRICAI.

Detection of Gas Leakage Sound Using Modular Neural Networks for Unknown Environments

Manabu Kotani, Seiichi Ozawa, Masanori Katsura, 2004, Neurocomputing.

Application of independent component analysis to handwritten Japanese character recognition

Norio Baba, Manabu Kotani, Seiichi Ozawa, 1999, IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339).

A subspace method for feature extraction using independent components

Manabu Kotani, Seiichi Ozawa, S. Kinukawa, 2002, Proceedings of the 41st SICE Annual Conference. SICE 2002..

One-Pass Incremental Membership Authentication by Face Classification

Shaoning Pang, Nikola K. Kasabov, Seiichi Ozawa, 2004, ICBA.

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

Tao Ban, Seiichi Ozawa, Jumpei Shimamura, 2014, 2014 Ninth Asia Joint Conference on Information Security.

Detecting Malicious Spam Mails: An Online Machine Learning Approach

Tao Ban, Seiichi Ozawa, Jumpei Shimamura, 2014, ICONIP.

Curiosity driven incremental LDA agent active learning

Shaoning Pang, Nikola K. Kasabov, Seiichi Ozawa, 2009, 2009 International Joint Conference on Neural Networks.

A Novel Incremental Linear Discriminant Analysis for Multitask Pattern Recognition Problems

Shaoning Pang, Nikola K. Kasabov, Seiichi Ozawa, 2008, ICONIP.

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

Seiichi Ozawa, Daisuke Higuchi, 2013, ICANN.

Fast Training of Three-Layered Neural Network Classifiers by Solving Inequalities

Naoki Tsuchiya, Shigeo Abe, Seiichi Ozawa, 2000 .

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

Nikola K. Kasabov, Seiichi Ozawa, Masayuki Hisada, 2010, Evol. Syst..

A Multitask Learning Model for Online Pattern Recognition

Seiichi Ozawa, Dmitri Roussinov, Asim Roy, 2009, IEEE Transactions on Neural Networks.

Redundancy Reduction of Features by Independent Component Analysis

Manabu Kotani, Seiichi Ozawa, Wataru Kusanagi, 2001 .

A Neural Network Model to Learn Multiple Tasks under Dynamic Environments

Seiichi Ozawa, Kenji Tsumori, 2010 .

Logo Detection With No Priors

F. Xavier Roca, Seiichi Ozawa, Josep M. Gonfaus, 2021, IEEE Access.

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

Seiichi Ozawa, Lihua Wang, Kengo Itokazu, 2021, 2021 International Joint Conference on Neural Networks (IJCNN).

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

Tao Ban, Seiichi Ozawa, Daisuke Inoue, 2021, ICONIP.

An Incremental Learning Algorithm of

Seiichi Ozawa, Recursive Fisher, 2009 .

An improvement of incremental recursive fisher linear discriminant for online feature extraction

Seiichi Ozawa, Ryohei Ohta, 2013 .

Feature extraction using supervised independent component analysis by maximizing class distance

Manabu Kotani, Seiichi Ozawa, Y. Sakaguchi, 2002, Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02..

Evolutionary discriminant functions using genetic algorithms with variable-length chromosome

Manabu Kotani, Seiichi Ozawa, Kenzo Akazawa, 2001, IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222).

A Study of Feature Extraction and Selection Using Independent Component Analysis

Seiichi Ozawa, S. Ozawa, 2000 .