| 2025 | PST | FragmentFool: Fragment-based Adversarial Perturbation for Graph Neural Network-based Vulnerability Detection. | Muhammad Fakhrur Rozi, Tao Ban, Seiichi Ozawa, Hiroaki Inoue, Takeshi Takahashi, Sajjad Dadkhah |
| 2024 | ICONIP | A Study on Time-Resilient Features for Detecting TLS Encrypted Malware Traffic. | Kaisei Fujiwara, Akira Yamada, Seiichi Ozawa, Chanho Park |
| 2022 | ICONIP | Permissioned Blockchain-Based XGBoost for Multi Banks Fraud Detection. | Septiviana Savitri Asrori, Lihua Wang, Seiichi Ozawa |
| 2021 | ICONIP | 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 |
| 2021 | IJCNN | Outlier Detection by Privacy-Preserving Ensemble Decision Tree U sing Homomorphic Encryption. | Kengo Itokazu, Lihua Wang, Seiichi Ozawa |
| 2020 | ICONIP | Port-Piece Embedding for Darknet Traffic Features and Clustering of Scan Attacks. | Shintaro Ishikawa, Seiichi Ozawa, Tao Ban |
| 2020 | ICONIP | New Approaches to Federated XGBoost Learning for Privacy-Preserving Data Analysis. | Fuki Yamamoto, Lihua Wang, Seiichi Ozawa |
| 2020 | IJCNN | 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 |
| 2020 | IJCNN | Deep Neural Networks for Malicious JavaScript Detection Using Bytecode Sequences. | Muhammad Fakhrur Rozi, Sangwook Kim, Seiichi Ozawa |
| 2019 | ICDM | A Fast Privacy-Preserving Multi-Layer Perceptron Using Ring-LWE-Based Homomorphic Encryption. | Takehiro Tezuka, Lihua Wang, Takuya Hayashi, Seiichi Ozawa |
| 2019 | ICONIP | Exploring and Identifying Malicious Sites in Dark Web Using Machine Learning. | Yuki Kawaguchi, Seiichi Ozawa |
| 2018 | ICONIP | Privacy-Preserving Naive Bayes Classification Using Fully Homomorphic Encryption. | Sangwook Kim, Masahiro Omori, Takuya Hayashi, Toshiaki Omori, Lihua Wang, Seiichi Ozawa |
| 2018 | IJCNN | A Machine Learning Approach to Malicious JavaScript Detection using Fixed Length Vector Representation. | Samuel Ndichu, Seiichi Ozawa, Takeshi Misu, Kouichirou Okada |
| 2018 | SMC | 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 |
| 2017 | ICONIP | AI Web-Contents Analyzer for Monitoring Underground Marketplace. | Yuki Kawaguchi, Akira Yamada, Seiichi Ozawa |
| 2017 | IJCNN | t-Distributed stochastic neighbor embedding spectral clustering. | Nicoleta Rogovschi, Jun Kitazono, Nistor Grozavu, Toshiaki Omori, Seiichi Ozawa |
| 2017 | IJCNN | 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 |
| 2016 | ICONIP | t-Distributed Stochastic Neighbor Embedding with Inhomogeneous Degrees of Freedom. | Jun Kitazono, Nistor Grozavu, Nicoleta Rogovschi, Toshiaki Omori, Seiichi Ozawa |
| 2016 | IJCNN | A neural network model for detecting DDoS attacks using darknet traffic features. | Siti Hajar Aminah Ali, Seiichi Ozawa, Tao Ban, Junji Nakazato, Jumpei Shimamura |
| 2016 | IJCNN | Stochastic collapsed variational Bayesian inference for biterm topic model. | Narutaka Awaya, Jun Kitazono, Toshiaki Omori, Seiichi Ozawa |
| 2015 | ICONIP | Adaptive DDoS-Event Detection from Big Darknet Traffic Data. | Nobuaki Furutani, Jun Kitazono, Seiichi Ozawa, Tao Ban, Junji Nakazato, Jumpei Shimamura |
| 2015 | IJCNN | An autonomous online malicious spam email detection system using extended RBF network. | Siti Hajar Aminah Ali, Seiichi Ozawa, Junji Nakazato, Tao Ban, Jumpei Shimamura |
| 2014 | ICONIP | Detecting Malicious Spam Mails: An Online Machine Learning Approach. | Yuli Dai, Shunsuke Tada, Tao Ban, Junji Nakazato, Jumpei Shimamura, Seiichi Ozawa |
| 2014 | IJCNN | A fast Incremental Kernel Principal Component Analysis for data streams. | Annie Anak Joseph, Seiichi Ozawa |
| 2013 | ICANN | A Neural Network Model for Online Multi-Task Multi-Label Pattern Recognition. | Daisuke Higuchi, Seiichi Ozawa |
| 2013 | ICONIP | A Neural Network Model for Large-Scale Stream Data Learning Using Locally Sensitive Hashing. | Siti Hajar Aminah Ali, Kiminori Fukase, Seiichi Ozawa |
| 2013 | IJCNN | A robust incremental principal component analysis for feature extraction from stream data with missing values. | Daijiro Aoki, Toshiaki Omori, Seiichi Ozawa |
| 2012 | ICMLA | A Sequential Multi-task Learning Neural Network with Metric-Based Knowledge Transfer. | Simeng Yue, Seiichi Ozawa |
| 2012 | ICONIP | Extension of Incremental Linear Discriminant Analysis to Online Feature Extraction under Nonstationary Environments. | Annie Anak Joseph, Young-Min Jang, Seiichi Ozawa, Minho Lee |
| 2011 | ICASSP | Incremental two-dimensional two-directional principal component analysis (I(2D) | Yonghwa Choi, Takaomi Tokumoto, Minho Lee, Seiichi Ozawa |
| 2011 | ICMLA | A Neural Network Model for Learning Data Stream with Multiple Class Labels. | Tomoyasu Takata, Seiichi Ozawa |
| 2011 | IJCNN | Incremental 2-directional 2-dimensional linear discriminant analysis for multitask pattern recognition. | Chunyu Liu, Young-Min Jang, Seiichi Ozawa, Minho Lee |
| 2011 | IJCNN | A fast incremental Kernel Principal Component Analysis for learning stream of data chunks. | Takaomi Tokumoto, Seiichi Ozawa |
| 2010 | IJCNN | An autonomous incremental learning algorithm of Resource Allocating Network for online pattern recognition. | Seiichi Ozawa, Sho Nakasaka, Asim Roy |
| 2010 | PRICAI | 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 |
| 2010 | PRICAI | A Fast Incremental Kernel Principal Component Analysis for Online Feature Extraction. | Seiichi Ozawa, Yohei Takeuchi, Shigeo Abe |
| 2009 | ICONIP | An Incremental Learning Algorithm for Resource Allocating Networks Based on Local Linear Regression. | Seiichi Ozawa, Keisuke Okamoto |
| 2009 | IJCNN | An incremental learning algorithm of Recursive Fisher Linear Discriminant. | Ryohei Ohta, Seiichi Ozawa |
| 2009 | IJCNN | Adaptive incremental principal component analysis in nonstationary online learning environments. | Seiichi Ozawa, Yuki Kawashima, Shaoning Pang, Nikola K. Kasabov |
| 2009 | IJCNN | Curiosity driven incremental LDA agent active learning. | Shaoning Pang, Seiichi Ozawa, Nikola K. Kasabov |
| 2009 | IDEAL | An Autonomous Learning Algorithm of Resource Allocating Network. | Toshihisa Tabuchi, Seiichi Ozawa, Asim Roy |
| 2009 | SMC | A Reinforcement Learning Model Using Macro-actions in Multi-task Grid-World Problems. | Seiichi Ozawa, Hiroshi Onda |
| 2008 | ICMLA | Incremental Learning for Multitask Pattern Recognition Problems. | Seiichi Ozawa, Asim Roy |
| 2008 | ICONIP | A Novel Incremental Linear Discriminant Analysis for Multitask Pattern Recognition Problems. | Masayuki Hisada, Seiichi Ozawa, Kau Zhang, Shaoning Pang, Nikola K. Kasabov |
| 2008 | ICONIP | A Neural Network Model for Sequential Multitask Pattern Recognition Problems. | Hitoshi Nishikawa, Seiichi Ozawa, Asim Roy |
| 2008 | ICONIP | Incremental Principal Component Analysis Based on Adaptive Accumulation Ratio. | Seiichi Ozawa, Kazuya Matsumoto, Shaoning Pang, Nikola K. Kasabov |
| 2007 | ICONIP | Adaptive Face Recognition System Using Fast Incremental Principal Component Analysis. | Seiichi Ozawa, Shaoning Pang, Nikola K. Kasabov |
| 2007 | IJCNN | An Efficient Incremental Kernel Principal Component Analysis for Online Feature Selection. | Yohei Takeuchi, Seiichi Ozawa, Shigeo Abe |
| 2006 | IJCNN | An Incremental Learning Algorithm of Ensemble Classifier Systems. | Takuya Kidera, Seiichi Ozawa, Shigeo Abe |
| 2005 | IJCNN | Incremental learning for online face recognition. | Seiichi Ozawa, Soon Lee Toh, Shigeo Abe, Shaoning Pang, Nikola K. Kasabov |
| 2005 | ISNN | Chunk Incremental LDA Computing on Data Streams. | Shaoning Pang, Seiichi Ozawa, Nikola K. Kasabov |
| 2004 | ICONIP | Supervised Independent Component Analysis with Class Information. | Manabu Kotani, Hiroki Takabatake, Seiichi Ozawa |
| 2004 | PRICAI | A Modified Incremental Principal Component Analysis for On-Line Learning of Feature Space and Classifier. | Seiichi Ozawa, Shaoning Pang, Nikola K. Kasabov |
| 2003 | IJCNN | A fast incremental learning algorithm of RBF networks with long-term memory. | Keisuke Okamoto, Seiichi Ozawa, Shigeo Abe |
| 2003 | IJCNN | Incremental learning in dynamic environments using neural network with long-term memory. | Kenji Tsumori, Seiichi Ozawa |
| 2003 | KES | Reinforcement Learning Using RBF Networks with Memory Mechanism. | Seiichi Ozawa, Naoto Shiraga |
| 2000 | IJCNN | Training Three-Layer Neural Network Classifiers by Solving Inequalities. | Naoki Tsuchiya, Seiichi Ozawa, Shigeo Abe |
| 1999 | IJCNN | Application of independent component analysis to feature extraction of speech. | Manabu Kotani, Yasunobu Shirata, Satoshi Maekawa, Seiichi Ozawa, Kenzo Akazawa |
| 1999 | IJCNN | Application of independent component analysis to handwritten Japanese character recognition. | Seiichi Ozawa, Toshihide Tsujimoto, Manabu Kotani, Norio Baba |
| 1999 | KES | Emergence of feature extraction function using genetic programming. | Manabu Kotani, Seiichi Ozawa, Masaki Nakai, Kenzo Akazawa |
| 1999 | KES | Evolution of a dynamical modular neural network and its application to associative memories. | Seiichi Ozawa, K. Tsutumi, Norio Baba |
| 1998 | ICONIP | Design of Modular Neural Network Architectures Using Genetic Algorithms. | Seiichi Ozawa, Kazuyoshi Tsutsumi, Norio Baba |