Seiichi Ozawa

ORCID

Publication Activity (10 Years)

Years Active: 1995-2024
Publications (10 Years): 39

Top Venues

Publications

Le Trieu Phong, Tran Thi Phuong, Lihua Wang, Seiichi Ozawa
Frameworks for Privacy-Preserving Federated Learning. IEICE Trans. Inf. Syst. 107 (1) (2024)
Miha Ozbot, Seiichi Ozawa, Igor Skrjanc
eFedGauss: A Federated Approach to Fuzzy Multivariate Gaussian Clustering. FUZZ (2024)
Enna Hirata, Takahiro Yamashita, Seiichi Ozawa
Researcher Network Visualization Using Matrix Researcher2vec. J. Adv. Comput. Intell. Intell. Informatics 27 (4) (2023)
Muhammad Fakhrur Rozi, Tao Ban, Seiichi Ozawa, Akira Yamada, Takeshi Takahashi, Sangwook Kim, Daisuke Inoue
Detecting Malicious JavaScript Using Structure-Based Analysis of Graph Representation. IEEE Access 11 (2023)
Fuki Yamamoto, Seiichi Ozawa, Lihua Wang
eFL-Boost: Efficient Federated Learning for Gradient Boosting Decision Trees. IEEE Access 10 (2022)
Parichehr Behjati, Pau Rodríguez, Carles Fernández Tena, Armin Mehri, F. Xavier Roca, Seiichi Ozawa, Jordi Gonzàlez
Frequency-Based Enhancement Network for Efficient Super-Resolution. IEEE Access 10 (2022)
Septiviana Savitri Asrori, Lihua Wang, Seiichi Ozawa
Permissioned Blockchain-Based XGBoost for Multi Banks Fraud Detection. ICONIP (3) (2022)
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
Privacy-Preserving Federated Learning for Detecting Fraudulent Financial Transactions in Japanese Banks. J. Inf. Process. 30 (2022)
Diego A. Velázquez, Josep M. Gonfaus, Pau Rodríguez, F. Xavier Roca, Seiichi Ozawa, Jordi Gonzàlez
Logo Detection With No Priors. IEEE Access 9 (2021)
Kengo Itokazu, Lihua Wang, Seiichi Ozawa
Outlier Detection by Privacy-Preserving Ensemble Decision Tree U sing Homomorphic Encryption. IJCNN (2021)
Muhammad Fakhrur Rozi, Tao Ban, Seiichi Ozawa, Sangwook Kim, Takeshi Takahashi, Daisuke Inoue
JStrack: Enriching Malicious JavaScript Detection Based on AST Graph Analysis and Attention Mechanism. ICONIP (2) (2021)
Seiichi Ozawa, Tao Ban, Naoki Hashimoto, Junji Nakazato, Jumpei Shimamura
A study of IoT malware activities using association rule learning for darknet sensor data. Int. J. Inf. Sec. 19 (1) (2020)
Samuel Ndichu, Sangwook Kim, Seiichi Ozawa
Deobfuscation, unpacking, and decoding of obfuscated malicious JavaScript for machine learning models detection performance improvement. CAAI Trans. Intell. Technol. 5 (3) (2020)
Shintaro Ishikawa, Seiichi Ozawa, Tao Ban
Port-Piece Embedding for Darknet Traffic Features and Clustering of Scan Attacks. ICONIP (2) (2020)
Fuki Yamamoto, Lihua Wang, Seiichi Ozawa
New Approaches to Federated XGBoost Learning for Privacy-Preserving Data Analysis. ICONIP (2) (2020)
Muhammad Fakhrur Rozi, Sangwook Kim, Seiichi Ozawa
Deep Neural Networks for Malicious JavaScript Detection Using Bytecode Sequences. IJCNN (2020)
Muhammad Taufiq Pratama, Sangwook Kim, Seiichi Ozawa, Takenao Ohkawa, Yuya Chonan, Hiroyuki Tsuji, Noriyuki Murakami
Deep Learning-based Object Detection for Crop Monitoring in Soybean Fields. IJCNN (2020)
Yuki Kawaguchi, Seiichi Ozawa
Exploring and Identifying Malicious Sites in Dark Web Using Machine Learning. ICONIP (3) (2019)
Samuel Ndichu, Sangwook Kim, Seiichi Ozawa, Takeshi Misu, Kazuo Makishima
A machine learning approach to detection of JavaScript-based attacks using AST features and paragraph vectors. Appl. Soft Comput. 84 (2019)
Takehiro Tezuka, Lihua Wang, Takuya Hayashi, Seiichi Ozawa
A Fast Privacy-Preserving Multi-Layer Perceptron Using Ring-LWE-Based Homomorphic Encryption. ICDM Workshops (2019)
Nicoleta Rogovschi, Sarah Zouinina, Basarab Matei, Issam Falih, Nistor Grozavu, Seiichi Ozawa
t-Distributed Stochastic Neighbor Embedding Spectral Clustering using higher order approximations. Aust. J. Intell. Inf. Process. Syst. 17 (1) (2019)
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
Editorial: Booming of Neural Networks and Learning Systems. IEEE Trans. Neural Networks Learn. Syst. 30 (1) (2019)
Igor Skrjanc, Seiichi Ozawa, Tao Ban, Dejan Dovzan
Large-scale cyber attacks monitoring using Evolving Cauchy Possibilistic Clustering. Appl. Soft Comput. 62 (2018)
Kazuki Omura, So Yahata, Seiichi Ozawa, Takenao Ohkawa, Yuya Chonan, Hiroyuki Tsuji, Noriyuki Murakami
An Image Sensing Method to Capture Soybean Growth State for Smart Agriculture Using Single Shot MultiBox Detector. SMC (2018)
Sangwook Kim, Masahiro Omori, Takuya Hayashi, Toshiaki Omori, Lihua Wang, Seiichi Ozawa
Privacy-Preserving Naive Bayes Classification Using Fully Homomorphic Encryption. ICONIP (4) (2018)
Naoki Hashimoto, Seiichi Ozawa, Tao Ban, Junji Nakazato, Jumpei Shimamura
A Darknet Traffic Analysis for IoT Malwares Using Association Rule Learning. INNS Conference on Big Data (2018)
Samuel Ndichu, Seiichi Ozawa, Takeshi Misu, Kouichirou Okada
A Machine Learning Approach to Malicious JavaScript Detection using Fixed Length Vector Representation. IJCNN (2018)
Yuki Kawaguchi, Akira Yamada, Seiichi Ozawa
AI Web-Contents Analyzer for Monitoring Underground Marketplace. ICONIP (5) (2017)
So Yahata, Tetsu Onishi, Kanta Yamaguchi, Seiichi Ozawa, Jun Kitazono, Takenao Ohkawa, Takeshi Yoshida, Noriyuki Murakami, Hiroyuki Tsuji
A hybrid machine learning approach to automatic plant phenotyping for smart agriculture. IJCNN (2017)
Igor Skrjanc, Seiichi Ozawa, Dejan Dovzan, Tao Ban, Junji Nakazato, Jumpei Shimamura
Evolving cauchy possibilistic clustering and its application to large-scale cyberattack monitoring. SSCI (2017)
Naoki Murata, Jun Kitazono, Seiichi Ozawa
Multidimensional Unfolding Based on Stochastic Neighbor Relationship. ICMLC (2017)
Shohei Kuri, Takuya Hayashi, Toshiaki Omori, Seiichi Ozawa, Yoshinori Aono, Le Trieu Phong, Lihua Wang, Shiho Moriai
Privacy preserving extreme learning machine using additively homomorphic encryption. SSCI (2017)
Nicoleta Rogovschi, Jun Kitazono, Nistor Grozavu, Toshiaki Omori, Seiichi Ozawa
t-Distributed stochastic neighbor embedding spectral clustering. IJCNN (2017)
Siti Hajar Aminah Ali, Kiminori Fukase, Seiichi Ozawa
A fast online learning algorithm of radial basis function network with locality sensitive hashing. Evol. Syst. 7 (3) (2016)
Seiichi Ozawa, Shun Yoshida, Jun Kitazono, Takahiro Sugawara, Tatsuya Haga
A sentiment polarity prediction model using transfer learning and its application to SNS flaming event detection. SSCI (2016)
Siti Hajar Aminah Ali, Seiichi Ozawa, Tao Ban, Junji Nakazato, Jumpei Shimamura
A neural network model for detecting DDoS attacks using darknet traffic features. IJCNN (2016)
Jun Kitazono, Nistor Grozavu, Nicoleta Rogovschi, Toshiaki Omori, Seiichi Ozawa
t-Distributed Stochastic Neighbor Embedding with Inhomogeneous Degrees of Freedom. ICONIP (3) (2016)
Annie Anak Joseph, Takaomi Tokumoto, Seiichi Ozawa
Online feature extraction based on accelerated kernel principal component analysis for data stream. Evol. Syst. 7 (1) (2016)
Narutaka Awaya, Jun Kitazono, Toshiaki Omori, Seiichi Ozawa
Stochastic collapsed variational Bayesian inference for biterm topic model. IJCNN (2016)
Nobuaki Furutani, Jun Kitazono, Seiichi Ozawa, Tao Ban, Junji Nakazato, Jumpei Shimamura
Adaptive DDoS-Event Detection from Big Darknet Traffic Data. ICONIP (4) (2015)
Hironori Nishikaze, Seiichi Ozawa, Jun Kitazono, Tao Ban, Junji Nakazato, Jumpei Shimamura
Large-Scale Monitoring for Cyber Attacks by Using Cluster Information on Darknet Traffic Features. INNS Conference on Big Data (2015)
Siti Hajar Aminah Ali, Seiichi Ozawa, Junji Nakazato, Tao Ban, Jumpei Shimamura
An autonomous online malicious spam email detection system using extended RBF network. IJCNN (2015)
Yuli Dai, Shunsuke Tada, Tao Ban, Junji Nakazato, Jumpei Shimamura, Seiichi Ozawa
Detecting Malicious Spam Mails: An Online Machine Learning Approach. ICONIP (3) (2014)
Yonghwa Choi, Seiichi Ozawa, Minho Lee
Incremental two-dimensional kernel principal component analysis. Neurocomputing 134 (2014)
Shun Yoshida, Jun Kitazono, Seiichi Ozawa, Takahiro Sugawara, Tatsuya Haga, Shogo Nakamura
Sentiment analysis for various SNS media using Naïve Bayes classifier and its application to flaming detection. CIBD (2014)
Annie Anak Joseph, Seiichi Ozawa
A fast Incremental Kernel Principal Component Analysis for data streams. IJCNN (2014)
Daisuke Higuchi, Seiichi Ozawa
A Neural Network Model for Semi-supervised Sequential Multi-task Learning in Multi-label Pattern Recognition Problems. IDT/IIMSS/STET (2014)
Nobuaki Furutani, Tao Ban, Junji Nakazato, Jumpei Shimamura, Jun Kitazono, Seiichi Ozawa
Detection of DDoS Backscatter Based on Traffic Features of Darknet TCP Packets. AsiaJCIS (2014)
Siti Hajar Aminah Ali, Kiminori Fukase, Seiichi Ozawa
A Neural Network Model for Large-Scale Stream Data Learning Using Locally Sensitive Hashing. ICONIP (1) (2013)
Daisuke Higuchi, Seiichi Ozawa
A Neural Network Model for Online Multi-Task Multi-Label Pattern Recognition. ICANN (2013)
Daijiro Aoki, Toshiaki Omori, Seiichi Ozawa
A robust incremental principal component analysis for feature extraction from stream data with missing values. IJCNN (2013)
Takaomi Tokumoto, Seiichi Ozawa
A property of learning chunk data using incremental kernel principal component analysis. EAIS (2012)
Simeng Yue, Seiichi Ozawa
A Sequential Multi-task Learning Neural Network with Metric-Based Knowledge Transfer. ICMLA (1) (2012)
Tomoyasu Takata, Daisuke Higuchi, Seiichi Ozawa
A sequential multitask learning algorithm for pattern recognition. ICDL-EPIROB (2012)
Annie Anak Joseph, Young-Min Jang, Seiichi Ozawa, Minho Lee
Extension of Incremental Linear Discriminant Analysis to Online Feature Extraction under Nonstationary Environments. ICONIP (2) (2012)
Yonghwa Choi, Takaomi Tokumoto, Minho Lee, Seiichi Ozawa
PCA) for face recognition. ICASSP (2011)
Tomoyasu Takata, Seiichi Ozawa
A Neural Network Model for Learning Data Stream with Multiple Class Labels. ICMLA (2) (2011)
Chunyu Liu, Young-Min Jang, Seiichi Ozawa, Minho Lee
Incremental 2-directional 2-dimensional linear discriminant analysis for multitask pattern recognition. IJCNN (2011)
Hitoshi Nishikawa, Seiichi Ozawa
Radial Basis Function Network for Multitask Pattern Recognition. Neural Process. Lett. 33 (3) (2011)
Young-Min Jang, Minho Lee, Seiichi Ozawa
A real-time personal authentication system based on incremental feature extraction and classification of audiovisual information. Evol. Syst. 2 (4) (2011)
Seiichi Ozawa, Ryohei Ohta
Incremental recursive fisher linear discriminant for online feature extraction. EAIS (2011)
Takaomi Tokumoto, Seiichi Ozawa
A fast incremental Kernel Principal Component Analysis for learning stream of data chunks. IJCNN (2011)
Seiichi Ozawa, Hisashi Handa
Guest editorial: Evolving autonomous systems under realistic environments. Evol. Syst. 2 (4) (2011)
Seiichi Ozawa, Sho Nakasaka, Asim Roy
An autonomous incremental learning algorithm of Resource Allocating Network for online pattern recognition. IJCNN (2010)
Seiichi Ozawa, Yohei Takeuchi, Shigeo Abe
A Fast Incremental Kernel Principal Component Analysis for Online Feature Extraction. PRICAI (2010)
Takashi Nagatani, Seiichi Ozawa, Shigeo Abe
Fast Variable Selection by Block Addition and Block Deletion. J. Intell. Learn. Syst. Appl. 2 (4) (2010)
Masayuki Hisada, Seiichi Ozawa, Kau Zhang, Nikola K. Kasabov
Incremental linear discriminant analysis for evolving feature spaces in multitask pattern recognition problems. Evol. Syst. 1 (1) (2010)
Seiichi Ozawa, Toshihisa Tabuchi, Sho Nakasaka, Asim Roy
An Autonomous Incremental Learning Algorithm for Radial Basis Function Networks. J. Intell. Learn. Syst. Appl. 2 (4) (2010)
Young-Min Jang, Seiichi Ozawa, Minho Lee
A Real-Time Personal Authentication System with Selective Attention and Incremental Learning Mechanism in Feature Extraction and Classifier. PRICAI (2010)
Toshihisa Tabuchi, Seiichi Ozawa, Asim Roy
An Autonomous Learning Algorithm of Resource Allocating Network. IDEAL (2009)
Seiichi Ozawa, Asim Roy, Dmitri Roussinov
A Multitask Learning Model for Online Pattern Recognition. IEEE Trans. Neural Networks 20 (3) (2009)
Shaoning Pang, Seiichi Ozawa, Nikola K. Kasabov
Curiosity driven incremental LDA agent active learning. IJCNN (2009)
Kazuya Morikawa, Seiichi Ozawa, Shigeo Abe
Tuning membership functions of kernel fuzzy classifiers by maximizing margins. Memetic Comput. 1 (3) (2009)
Seiichi Ozawa, Keisuke Okamoto
An Incremental Learning Algorithm for Resource Allocating Networks Based on Local Linear Regression. ICONIP (1) (2009)
Seiichi Ozawa, Yuki Kawashima, Shaoning Pang, Nikola K. Kasabov
Adaptive incremental principal component analysis in nonstationary online learning environments. IJCNN (2009)
Ryohei Ohta, Seiichi Ozawa
An incremental learning algorithm of Recursive Fisher Linear Discriminant. IJCNN (2009)
Seiichi Ozawa, Hiroshi Onda
A Reinforcement Learning Model Using Macro-actions in Multi-task Grid-World Problems. SMC (2009)
Hitoshi Nishikawa, Seiichi Ozawa, Asim Roy
A Neural Network Model for Sequential Multitask Pattern Recognition Problems. ICONIP (1) (2008)
Seiichi Ozawa, Asim Roy
Incremental Learning for Multitask Pattern Recognition Problems. ICMLA (2008)
Masayuki Hisada, Seiichi Ozawa, Kau Zhang, Shaoning Pang, Nikola K. Kasabov
A Novel Incremental Linear Discriminant Analysis for Multitask Pattern Recognition Problems. ICONIP (1) (2008)
Seiichi Ozawa, Kazuya Matsumoto, Shaoning Pang, Nikola K. Kasabov
Incremental Principal Component Analysis Based on Adaptive Accumulation Ratio. ICONIP (1) (2008)
Seiichi Ozawa, Shaoning Pang, Nikola K. Kasabov
Incremental Learning of Chunk Data for Online Pattern Classification Systems. IEEE Trans. Neural Networks 19 (6) (2008)
Seiichi Ozawa, Shaoning Pang, Nikola K. Kasabov
Adaptive Face Recognition System Using Fast Incremental Principal Component Analysis. ICONIP (2) (2007)
Yohei Takeuchi, Seiichi Ozawa, Shigeo Abe
An Efficient Incremental Kernel Principal Component Analysis for Online Feature Selection. IJCNN (2007)
Shinji Kita, Seiichi Ozawa, Satoshi Maekawa, Shigeo Abe
A Learning Algorithm of Boosting Kernel Discriminant Analysis for Pattern Recognition. IEICE Trans. Inf. Syst. (11) (2007)
Seiichi Ozawa, Shaoning Pang, Nikola K. Kasabov
An Incremental Principal Component Analysis for Chunk Data. FUZZ-IEEE (2006)
Seiichi Ozawa, Shaoning Pang, Nikola K. Kasabov
Incremental learning of feature space and classifier for on-line pattern recognition. Int. J. Knowl. Based Intell. Eng. Syst. 10 (1) (2006)
Takuya Kidera, Seiichi Ozawa, Shigeo Abe
An Incremental Learning Algorithm of Ensemble Classifier Systems. IJCNN (2006)
Seiichi Ozawa, Soon Lee Toh, Shigeo Abe, Shaoning Pang, Nikola K. Kasabov
Incremental learning of feature space and classifier for face recognition. Neural Networks 18 (5-6) (2005)
Shosuke Kimura, Seiichi Ozawa, Shigeo Abe
Incremental Kernel PCA for Online Learning of Feature Space. CIMCA/IAWTIC (2005)
Shaoning Pang, Seiichi Ozawa, Nikola K. Kasabov
Chunk Incremental LDA Computing on Data Streams. ISNN (2) (2005)
Manabu Kotani, Seiichi Ozawa
Feature Extraction Using Independent Components of Each Category. Neural Process. Lett. 22 (2) (2005)
Shaoning Pang, Seiichi Ozawa, Nikola K. Kasabov
Incremental linear discriminant analysis for classification of data streams. IEEE Trans. Syst. Man Cybern. Part B 35 (5) (2005)
Seiichi Ozawa, Shaoning Pang, Nikola K. Kasabov
A Modified Incremental Principal Component Analysis for On-Line Learning of Feature Space and Classifier. PRICAI (2004)
Manabu Kotani, Hiroki Takabatake, Seiichi Ozawa
Supervised Independent Component Analysis with Class Information. ICONIP (2004)
Manabu Kotani, Masanori Katsura, Seiichi Ozawa
Detection of gas leakage sound using modular neural networks for unknown environments. Neurocomputing 62 (2004)
Shaoning Pang, Seiichi Ozawa, Nikola K. Kasabov
One-Pass Incremental Membership Authentication by Face Classification. ICBA (2004)
Seiichi Ozawa, Kenji Tsumori
A memory-based neural network model for efficient adaptation to dynamic environments. FUZZ-IEEE (2004)
Seiichi Ozawa, Naoto Shiraga
Reinforcement Learning Using RBF Networks with Memory Mechanism. KES (2003)
Naoki Tsuchiya, Seiichi Ozawa, Shigeo Abe
Training Three-Layer Neural Network Classifiers by Solving Inequalities. IJCNN (3) (2000)

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Publication Activity (10 Years)

Top Topics

Top Venues

Seiichi Ozawa