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2020 – today
- 2024
[j35]Muhammad Fakhrur Rozi
, Tao Ban, Seiichi Ozawa, Akira Yamada, Takeshi Takahashi, Daisuke Inoue:
Securing Code With Context: Enhancing Vulnerability Detection Through Contextualized Graph Representations. IEEE Access 12: 142101-142126 (2024)- [j34]Le Trieu Phong, Tran Thi Phuong, Lihua Wang, Seiichi Ozawa:
Frameworks for Privacy-Preserving Federated Learning. IEICE Trans. Inf. Syst. 107(1): 2-12 (2024) - [c74]Miha Ozbot, Seiichi Ozawa, Igor Skrjanc:
eFedGauss: A Federated Approach to Fuzzy Multivariate Gaussian Clustering. FUZZ 2024: 1-8 - 2023
- [j33]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: 102727-102745 (2023) - [j32]Enna Hirata, Takahiro Yamashita, Seiichi Ozawa:
Researcher Network Visualization Using Matrix Researcher2vec. J. Adv. Comput. Intell. Intell. Informatics 27(4): 603-608 (2023) - [e19]Mohammad Tanveer, Sonali Agarwal, Seiichi Ozawa, Asif Ekbal, Adam Jatowt:
Neural Information Processing - 29th International Conference, ICONIP 2022, Virtual Event, November 22-26, 2022, Proceedings, Part IV. Communications in Computer and Information Science 1791, Springer 2023, ISBN 978-981-99-1638-2 [contents] - [e18]Mohammad Tanveer, Sonali Agarwal, Seiichi Ozawa, Asif Ekbal, Adam Jatowt:
Neural Information Processing - 29th International Conference, ICONIP 2022, Virtual Event, November 22-26, 2022, Proceedings, Part V. Communications in Computer and Information Science 1792, Springer 2023, ISBN 978-981-99-1641-2 [contents] - [e17]Mohammad Tanveer, Sonali Agarwal, Seiichi Ozawa, Asif Ekbal, Adam Jatowt:
Neural Information Processing - 29th International Conference, ICONIP 2022, Virtual Event, November 22-26, 2022, Proceedings, Part VI. Communications in Computer and Information Science 1793, Springer 2023, ISBN 978-981-99-1644-3 [contents] - [e16]Mohammad Tanveer, Sonali Agarwal, Seiichi Ozawa, Asif Ekbal, Adam Jatowt:
Neural Information Processing - 29th International Conference, ICONIP 2022, Virtual Event, November 22-26, 2022, Proceedings, Part VII. Communications in Computer and Information Science 1794, Springer 2023, ISBN 978-981-99-1647-4 [contents] - [e15]Mohammad Tanveer, Sonali Agarwal, Seiichi Ozawa, Asif Ekbal, Adam Jatowt:
Neural Information Processing - 29th International Conference, ICONIP 2022, Virtual Event, November 22-26, 2022, Proceedings, Part I. Lecture Notes in Computer Science 13623, Springer 2023, ISBN 978-3-031-30104-9 [contents] - [e14]Mohammad Tanveer, Sonali Agarwal, Seiichi Ozawa, Asif Ekbal, Adam Jatowt:
Neural Information Processing - 29th International Conference, ICONIP 2022, Virtual Event, November 22-26, 2022, Proceedings, Part II. Lecture Notes in Computer Science 13624, Springer 2023, ISBN 978-3-031-30107-0 [contents] - [e13]Mohammad Tanveer, Sonali Agarwal, Seiichi Ozawa, Asif Ekbal, Adam Jatowt:
Neural Information Processing - 29th International Conference, ICONIP 2022, Virtual Event, November 22-26, 2022, Proceedings, Part III. Lecture Notes in Computer Science 13625, Springer 2023, ISBN 978-3-031-30110-0 [contents] - 2022
- [j31]Fuki Yamamoto, Seiichi Ozawa, Lihua Wang:
eFL-Boost: Efficient Federated Learning for Gradient Boosting Decision Trees. IEEE Access 10: 43954-43963 (2022) - [j30]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: 57383-57397 (2022) - [j29]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: 789-795 (2022) - [c73]Septiviana Savitri Asrori, Lihua Wang, Seiichi Ozawa:
Permissioned Blockchain-Based XGBoost for Multi Banks Fraud Detection. ICONIP (3) 2022: 683-692 - 2021
- [j28]Diego A. Velázquez, Josep M. Gonfaus, Pau Rodríguez, F. Xavier Roca, Seiichi Ozawa, Jordi Gonzàlez:
Logo Detection With No Priors. IEEE Access 9: 106998-107011 (2021) - [c72]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: 669-680 - [c71]Kengo Itokazu, Lihua Wang, Seiichi Ozawa:
Outlier Detection by Privacy-Preserving Ensemble Decision Tree U sing Homomorphic Encryption. IJCNN 2021: 1-7 - 2020
- [j27]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): 184-192 (2020) - [j26]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): 83-92 (2020) - [c70]Fuki Yamamoto, Lihua Wang, Seiichi Ozawa:
New Approaches to Federated XGBoost Learning for Privacy-Preserving Data Analysis. ICONIP (2) 2020: 558-569 - [c69]Shintaro Ishikawa, Seiichi Ozawa, Tao Ban:
Port-Piece Embedding for Darknet Traffic Features and Clustering of Scan Attacks. ICONIP (2) 2020: 593-603 - [c68]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: 1-7 - [c67]Muhammad Fakhrur Rozi, Sangwook Kim, Seiichi Ozawa:
Deep Neural Networks for Malicious JavaScript Detection Using Bytecode Sequences. IJCNN 2020: 1-8
2010 – 2019
- 2019
- [j25]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): 78-86 (2019) - [j24]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) - [j23]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): 2-10 (2019) - [c66]Takehiro Tezuka, Lihua Wang, Takuya Hayashi, Seiichi Ozawa:
A Fast Privacy-Preserving Multi-Layer Perceptron Using Ring-LWE-Based Homomorphic Encryption. ICDM Workshops 2019: 37-44 - [c65]Yuki Kawaguchi, Seiichi Ozawa:
Exploring and Identifying Malicious Sites in Dark Web Using Machine Learning. ICONIP (3) 2019: 319-327 - 2018
- [j22]Igor Skrjanc, Seiichi Ozawa, Tao Ban, Dejan Dovzan:
Large-scale cyber attacks monitoring using Evolving Cauchy Possibilistic Clustering. Appl. Soft Comput. 62: 592-601 (2018) - [c64]Sangwook Kim, Masahiro Omori, Takuya Hayashi, Toshiaki Omori, Lihua Wang, Seiichi Ozawa:
Privacy-Preserving Naive Bayes Classification Using Fully Homomorphic Encryption. ICONIP (4) 2018: 349-358 - [c63]Samuel Ndichu, Seiichi Ozawa, Takeshi Misu, Kouichirou Okada:
A Machine Learning Approach to Malicious JavaScript Detection using Fixed Length Vector Representation. IJCNN 2018: 1-8 - [c62]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: 118-123 - [c61]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: 1693-1698 - [e12]Long Cheng, Andrew Chi-Sing Leung, Seiichi Ozawa:
Neural Information Processing - 25th International Conference, ICONIP 2018, Siem Reap, Cambodia, December 13-16, 2018, Proceedings, Part I. Lecture Notes in Computer Science 11301, Springer 2018, ISBN 978-3-030-04166-3 [contents] - [e11]Long Cheng, Andrew Chi-Sing Leung, Seiichi Ozawa:
Neural Information Processing - 25th International Conference, ICONIP 2018, Siem Reap, Cambodia, December 13-16, 2018, Proceedings, Part II. Lecture Notes in Computer Science 11302, Springer 2018, ISBN 978-3-030-04178-6 [contents] - [e10]Long Cheng, Andrew Chi-Sing Leung, Seiichi Ozawa:
Neural Information Processing - 25th International Conference, ICONIP 2018, Siem Reap, Cambodia, December 13-16, 2018, Proceedings, Part III. Lecture Notes in Computer Science 11303, Springer 2018, ISBN 978-3-030-04181-6 [contents] - [e9]Long Cheng, Andrew Chi-Sing Leung, Seiichi Ozawa:
Neural Information Processing - 25th International Conference, ICONIP 2018, Siem Reap, Cambodia, December 13-16, 2018, Proceedings, Part IV. Lecture Notes in Computer Science 11304, Springer 2018, ISBN 978-3-030-04211-0 [contents] - [e8]Long Cheng, Andrew Chi-Sing Leung, Seiichi Ozawa:
Neural Information Processing - 25th International Conference, ICONIP 2018, Siem Reap, Cambodia, December 13-16, 2018, Proceedings, Part V. Lecture Notes in Computer Science 11305, Springer 2018, ISBN 978-3-030-04220-2 [contents] - [e7]Long Cheng, Andrew Chi-Sing Leung, Seiichi Ozawa:
Neural Information Processing - 25th International Conference, ICONIP 2018, Siem Reap, Cambodia, December 13-16, 2018, Proceedings, Part VI. Lecture Notes in Computer Science 11306, Springer 2018, ISBN 978-3-030-04223-3 [contents] - [e6]Long Cheng, Andrew Chi-Sing Leung, Seiichi Ozawa:
Neural Information Processing - 25th International Conference, ICONIP 2018, Siem Reap, Cambodia, December 13-16, 2018, Proceedings, Part VII. Lecture Notes in Computer Science 11307, Springer 2018, ISBN 978-3-030-04238-7 [contents] - [e5]Seiichi Ozawa, Ah-Hwee Tan, Plamen P. Angelov, Asim Roy, Mahardhika Pratama:
INNS Conference on Big Data and Deep Learning 2018, Sanur, Bali, Indonesia, 17-19 April 2018. Procedia Computer Science 144, Elsevier 2018 [contents] - 2017
- [c60]Naoki Murata, Jun Kitazono, Seiichi Ozawa:
Multidimensional Unfolding Based on Stochastic Neighbor Relationship. ICMLC 2017: 248-252 - [c59]Yuki Kawaguchi, Akira Yamada, Seiichi Ozawa:
AI Web-Contents Analyzer for Monitoring Underground Marketplace. ICONIP (5) 2017: 888-896 - [c58]Nicoleta Rogovschi, Jun Kitazono, Nistor Grozavu, Toshiaki Omori, Seiichi Ozawa:
t-Distributed stochastic neighbor embedding spectral clustering. IJCNN 2017: 1628-1632 - [c57]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: 1787-1793 - [c56]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: 1-8 - [c55]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: 1-7 - 2016
- [j21]Annie Anak Joseph, Takaomi Tokumoto, Seiichi Ozawa:
Online feature extraction based on accelerated kernel principal component analysis for data stream. Evol. Syst. 7(1): 15-27 (2016) - [j20]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): 173-186 (2016) - [c54]Jun Kitazono, Nistor Grozavu, Nicoleta Rogovschi, Toshiaki Omori, Seiichi Ozawa:
t-Distributed Stochastic Neighbor Embedding with Inhomogeneous Degrees of Freedom. ICONIP (3) 2016: 119-128 - [c53]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: 2979-2985 - [c52]Narutaka Awaya, Jun Kitazono, Toshiaki Omori, Seiichi Ozawa:
Stochastic collapsed variational Bayesian inference for biterm topic model. IJCNN 2016: 3364-3370 - [c51]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: 1-7 - [e4]Akira Hirose, Seiichi Ozawa, Kenji Doya, Kazushi Ikeda, Minho Lee, Derong Liu:
Neural Information Processing - 23rd International Conference, ICONIP 2016, Kyoto, Japan, October 16-21, 2016, Proceedings, Part I. Lecture Notes in Computer Science 9947, 2016, ISBN 978-3-319-46686-6 [contents] - [e3]Akira Hirose, Seiichi Ozawa, Kenji Doya, Kazushi Ikeda, Minho Lee, Derong Liu:
Neural Information Processing - 23rd International Conference, ICONIP 2016, Kyoto, Japan, October 16-21, 2016, Proceedings, Part II. Lecture Notes in Computer Science 9948, 2016, ISBN 978-3-319-46671-2 [contents] - [e2]Akira Hirose, Seiichi Ozawa, Kenji Doya, Kazushi Ikeda, Minho Lee, Derong Liu:
Neural Information Processing - 23rd International Conference, ICONIP 2016, Kyoto, Japan, October 16-21, 2016, Proceedings, Part III. Lecture Notes in Computer Science 9949, 2016, ISBN 978-3-319-46674-3 [contents] - [e1]Akira Hirose, Seiichi Ozawa, Kenji Doya, Kazushi Ikeda, Minho Lee, Derong Liu:
Neural Information Processing - 23rd International Conference, ICONIP 2016, Kyoto, Japan, October 16-21, 2016, Proceedings, Part IV. Lecture Notes in Computer Science 9950, 2016, ISBN 978-3-319-46680-4 [contents] - 2015
- [c50]Nobuaki Furutani, Jun Kitazono, Seiichi Ozawa, Tao Ban, Junji Nakazato, Jumpei Shimamura:
Adaptive DDoS-Event Detection from Big Darknet Traffic Data. ICONIP (4) 2015: 376-383 - [c49]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: 1-7 - [c48]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: 175-182 - 2014
- [j19]Yonghwa Choi, Seiichi Ozawa, Minho Lee:
Incremental two-dimensional kernel principal component analysis. Neurocomputing 134: 280-288 (2014) - [c47]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: 39-43 - [c46]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: 20-25 - [c45]Yuli Dai, Shunsuke Tada, Tao Ban, Junji Nakazato, Jumpei Shimamura, Seiichi Ozawa:
Detecting Malicious Spam Mails: An Online Machine Learning Approach. ICONIP (3) 2014: 365-372 - [c44]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: 402-411 - [c43]Annie Anak Joseph, Seiichi Ozawa:
A fast Incremental Kernel Principal Component Analysis for data streams. IJCNN 2014: 3135-3142 - 2013
- [c42]Daisuke Higuchi, Seiichi Ozawa:
A Neural Network Model for Online Multi-Task Multi-Label Pattern Recognition. ICANN 2013: 162-169 - [c41]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: 369-376 - [c40]Daijiro Aoki, Toshiaki Omori, Seiichi Ozawa:
A robust incremental principal component analysis for feature extraction from stream data with missing values. IJCNN 2013: 1-8 - 2012
- [c39]Takaomi Tokumoto, Seiichi Ozawa:
A property of learning chunk data using incremental kernel principal component analysis. EAIS 2012: 7-10 - [c38]Tomoyasu Takata, Daisuke Higuchi, Seiichi Ozawa:
A sequential multitask learning algorithm for pattern recognition. ICDL-EPIROB 2012: 1-2 - [c37]Simeng Yue, Seiichi Ozawa:
A Sequential Multi-task Learning Neural Network with Metric-Based Knowledge Transfer. ICMLA (1) 2012: 671-674 - [c36]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: 640-647 - 2011
- [j18]Seiichi Ozawa, Hisashi Handa:
Guest editorial: Evolving autonomous systems under realistic environments. Evol. Syst. 2(4): 215-217 (2011) - [j17]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): 261-272 (2011) - [j16]Hitoshi Nishikawa, Seiichi Ozawa:
Radial Basis Function Network for Multitask Pattern Recognition. Neural Process. Lett. 33(3): 283-299 (2011) - [c35]Seiichi Ozawa, Ryohei Ohta:
Incremental recursive fisher linear discriminant for online feature extraction. EAIS 2011: 70-76 - [c34]Yonghwa Choi, Takaomi Tokumoto, Minho Lee, Seiichi Ozawa:
Incremental two-dimensional two-directional principal component analysis (I(2D)2PCA) for face recognition. ICASSP 2011: 1493-1496 - [c33]Tomoyasu Takata, Seiichi Ozawa:
A Neural Network Model for Learning Data Stream with Multiple Class Labels. ICMLA (2) 2011: 35-40 - [c32]Takaomi Tokumoto, Seiichi Ozawa:
A fast incremental Kernel Principal Component Analysis for learning stream of data chunks. IJCNN 2011: 2881-2888 - [c31]Chunyu Liu, Young-Min Jang, Seiichi Ozawa, Minho Lee:
Incremental 2-directional 2-dimensional linear discriminant analysis for multitask pattern recognition. IJCNN 2011: 2911-2916 - 2010
- [j15]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): 17-27 (2010) - [j14]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): 179-189 (2010) - [j13]Takashi Nagatani, Seiichi Ozawa, Shigeo Abe:
Fast Variable Selection by Block Addition and Block Deletion. J. Intell. Learn. Syst. Appl. 2(4): 200-211 (2010) - [c30]Seiichi Ozawa, Sho Nakasaka, Asim Roy:
An autonomous incremental learning algorithm of Resource Allocating Network for online pattern recognition. IJCNN 2010: 1-8 - [c29]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: 445-455 - [c28]Seiichi Ozawa, Yohei Takeuchi, Shigeo Abe:
A Fast Incremental Kernel Principal Component Analysis for Online Feature Extraction. PRICAI 2010: 487-497
2000 – 2009
- 2009
- [j12]Kazuya Morikawa, Seiichi Ozawa, Shigeo Abe:
Tuning membership functions of kernel fuzzy classifiers by maximizing margins. Memetic Comput. 1(3): 221-228 (2009) - [j11]Seiichi Ozawa, Asim Roy, Dmitri Roussinov:
A Multitask Learning Model for Online Pattern Recognition. IEEE Trans. Neural Networks 20(3): 430-445 (2009) - [c27]Seiichi Ozawa, Keisuke Okamoto:
An Incremental Learning Algorithm for Resource Allocating Networks Based on Local Linear Regression. ICONIP (1) 2009: 562-569 - [c26]Toshihisa Tabuchi, Seiichi Ozawa, Asim Roy:
An Autonomous Learning Algorithm of Resource Allocating Network. IDEAL 2009: 134-141 - [c25]Ryohei Ohta, Seiichi Ozawa:
An incremental learning algorithm of Recursive Fisher Linear Discriminant. IJCNN 2009: 2310-2315 - [c24]Seiichi Ozawa, Yuki Kawashima, Shaoning Pang, Nikola K. Kasabov:
Adaptive incremental principal component analysis in nonstationary online learning environments. IJCNN 2009: 2394-2400 - [c23]Shaoning Pang, Seiichi Ozawa, Nikola K. Kasabov:
Curiosity driven incremental LDA agent active learning. IJCNN 2009: 2401-2408 - [c22]Seiichi Ozawa, Hiroshi Onda:
A Reinforcement Learning Model Using Macro-actions in Multi-task Grid-World Problems. SMC 2009: 3088-3093 - 2008
- [j10]Seiichi Ozawa, Shaoning Pang, Nikola K. Kasabov:
Incremental Learning of Chunk Data for Online Pattern Classification Systems. IEEE Trans. Neural Networks 19(6): 1061-1074 (2008) - [c21]Seiichi Ozawa, Asim Roy:
Incremental Learning for Multitask Pattern Recognition Problems. ICMLA 2008: 747-751 - [c20]Hitoshi Nishikawa, Seiichi Ozawa, Asim Roy:
A Neural Network Model for Sequential Multitask Pattern Recognition Problems. ICONIP (1) 2008: 821-828 - [c19]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: 1163-1171 - [c18]Seiichi Ozawa, Kazuya Matsumoto, Shaoning Pang, Nikola K. Kasabov:
Incremental Principal Component Analysis Based on Adaptive Accumulation Ratio. ICONIP (1) 2008: 1196-1203 - 2007
- [j9]Shinji Kita, Seiichi Ozawa, Satoshi Maekawa, Shigeo Abe:
A Learning Algorithm of Boosting Kernel Discriminant Analysis for Pattern Recognition. IEICE Trans. Inf. Syst. 90-D(11): 1853-1863 (2007) - [c17]Seiichi Ozawa, Shaoning Pang, Nikola K. Kasabov:
Adaptive Face Recognition System Using Fast Incremental Principal Component Analysis. ICONIP (2) 2007: 396-405 - [c16]Yohei Takeuchi, Seiichi Ozawa, Shigeo Abe:
An Efficient Incremental Kernel Principal Component Analysis for Online Feature Selection. IJCNN 2007: 2346-2351 - 2006
- [j8]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): 57-65 (2006) - [c15]Seiichi Ozawa, Shaoning Pang, Nikola K. Kasabov:
An Incremental Principal Component Analysis for Chunk Data. FUZZ-IEEE 2006: 2278-2285 - [c14]Takuya Kidera, Seiichi Ozawa, Shigeo Abe:
An Incremental Learning Algorithm of Ensemble Classifier Systems. IJCNN 2006: 3421-3427 - 2005
- [j7]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): 575-584 (2005) - [j6]Manabu Kotani, Seiichi Ozawa:
Feature Extraction Using Independent Components of Each Category. Neural Process. Lett. 22(2): 113-124 (2005) - [j5]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): 905-914 (2005) - [c13]Shosuke Kimura, Seiichi Ozawa, Shigeo Abe:
Incremental Kernel PCA for Online Learning of Feature Space. CIMCA/IAWTIC 2005: 595-600 - [c12]Shaoning Pang, Seiichi Ozawa, Nikola K. Kasabov:
Chunk Incremental LDA Computing on Data Streams. ISNN (2) 2005: 51-56 - 2004
- [j4]Manabu Kotani, Masanori Katsura, Seiichi Ozawa:
Detection of gas leakage sound using modular neural networks for unknown environments. Neurocomputing 62: 427-440 (2004) - [c11]Seiichi Ozawa, Kenji Tsumori:
A memory-based neural network model for efficient adaptation to dynamic environments. FUZZ-IEEE 2004: 437-442 - [c10]Shaoning Pang, Seiichi Ozawa, Nikola K. Kasabov:
One-Pass Incremental Membership Authentication by Face Classification. ICBA 2004: 155-161 - [c9]Manabu Kotani, Hiroki Takabatake, Seiichi Ozawa:
Supervised Independent Component Analysis with Class Information. ICONIP 2004: 1052-1057 - [c8]Seiichi Ozawa, Shaoning Pang, Nikola K. Kasabov:
A Modified Incremental Principal Component Analysis for On-Line Learning of Feature Space and Classifier. PRICAI 2004: 231-240 - 2003
- [c7]Seiichi Ozawa, Naoto Shiraga:
Reinforcement Learning Using RBF Networks with Memory Mechanism. KES 2003: 1149-1156 - 2000
- [c6]Naoki Tsuchiya, Seiichi Ozawa, Shigeo Abe:
Training Three-Layer Neural Network Classifiers by Solving Inequalities. IJCNN (3) 2000: 555-560
1990 – 1999
- 1999
- [j3]Seiichi Ozawa, Kazuyoshi Tsutsumi, Norio Baba:
A Continuous-Time Model of Autoassociative Neural Memories Utilizing the Noise-Subspace Dynamics. Neural Process. Lett. 10(2): 97-109 (1999) - [c5]Seiichi Ozawa, Toshihide Tsujimoto, Manabu Kotani, Norio Baba:
Application of independent component analysis to handwritten Japanese character recognition. IJCNN 1999: 2867-2871 - [c4]Manabu Kotani, Yasunobu Shirata, Satoshi Maekawa, Seiichi Ozawa, Kenzo Akazawa:
Application of independent component analysis to feature extraction of speech. IJCNN 1999: 2981-2984 - [c3]Seiichi Ozawa, K. Tsutumi, Norio Baba:
Evolution of a dynamical modular neural network and its application to associative memories. KES 1999: 145-148 - [c2]Manabu Kotani, Seiichi Ozawa, Masaki Nakai, Kenzo Akazawa:
Emergence of feature extraction function using genetic programming. KES 1999: 149-152 - 1998
- [j2]Seiichi Ozawa, Kazuyoshi Tsutsumi, Norio Baba:
An artificial modular neural network and its basic dynamical characteristics. Biol. Cybern. 78(1): 19-36 (1998) - [c1]Seiichi Ozawa, Kazuyoshi Tsutsumi, Norio Baba:
Design of Modular Neural Network Architectures Using Genetic Algorithms. ICONIP 1998: 1608-1611 - 1995
- [j1]Seiichi Ozawa, Kazuyoshi Tsutsumi:
A multimodule neural network model and the estimate of its nature as associative memory. Syst. Comput. Jpn. 26(1): 99-110 (1995)
Coauthor Index
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