| 1. |
Yiluo Liu, Yaokai Feng, Kouichi Sakurai
, A Design of Internet of Vehicles System Incorporating Lightweight Roadside Units and Blockchain Strategy, The 18th International Conference on Ubiquitous Information Management and Communication, IEEE, 10.1109/IMCOM60618.2024.10418375, 1-8, 2024.01. |
| 2. |
Pengju He, Haibo Zhang, Yaokai Feng, Kouichi Sakurai, A Design of Network Attack Detection Using Causal and Non-causal Temporal Convolutional, The 5th International Conference on Science of Cyber Security, LNCS,volume 14299, 513-523, Springer,, https://doi.org/10.1007/978-3-031-45933-7_30, 2023.07. |
| 3. |
Yang Lyu, Yaokai Feng, Kouichi Sakurai, A Survey on Feature Selection Techniques Based on Filtering Methods for Cyber Attack Detection, Information, https://doi.org/10.3390/info14030191, 14, 3, 191, 2023.03.  |
| 4. |
Yang Lyu, Yaokai Feng, Kouichi Sakurai, Filter-based Feature Selection Techniques for Network Anomaly Detection, 4th International Symposium on AI Electronics, 2023.02. |
| 5. |
Muyuan Niu, Yaokai Feng, Kouichi Sakurai, A two-stage detection system of DDoS attacks in SDN using a trigger with multiple features and self-adaptive thresholds, 17th International Conference on Ubiquitous Information Management and Communication, IEEE,, ISBN 978-1-6654-5348-6,, DOI: 10.1109/IMCOM56909.2023, 1-7, 2023.01. |
| 6. |
Xiaojuan Cai, Yaokai Feng, Kouichi Sakurai, A Scheme Using a Classification Filter for the Sequential Detection of Cyber-attacks, Proc. the 6th IEEE CyberSciTech 2021, 2021.10. |
| 7. |
Tao Wang, Yaokai Feng, Kouichi Sakurai, Improving the Two-stage Detection of Cyberattacks in SDN Environment Using Dynamic Thresholding, 15th International Conference on Ubiquitous Information Management and Communication, IEEE, , 10.1109/IMCOM51814.2021.9377395, ISBN 978-1-6654-2318-2, 1-7, 2021.01. |
| 8. |
Yan Naung Soe, Yaokai Feng, Paulus Insap Santosa, Rudy Hartanto, Kouichi Sakurai, Machine Learning-Based IoT-Botnet Attacks Detection with Sequential
Architecture, Sensors 20(16), 2020, doi.org/10.3390/s20164372, 2020.09. |
| 9. |
Hao Zhao, Yaokai Feng, Hiroshi Koide, Kouichi Sakurai, A Sequential Detection Method for Intrusion Detection System Based on Artificial Neural Networks, Int. J. Netw. Comput. 10(2): 213-226 (2020), doi.org/10.15803/ijnc.10.2_213, 2020.08. |
| 10. |
Yan Naung Soe, Yaokai Feng, Paulus Insap Santosa, Rudy Hartanto, Kouichi Sakurai, Towards a Lightweight Detection System for Cyber Attacks in the IoT Environment Using Corresponding Features, Electronics 2020, 9(1), 144 (19 pages), doi.org/10.3390/electronics9010144, 9, 2020.01. |
| 11. |
Hao Zhao, Yaokai Feng, Kouichi Sakurai,, An ANN Based Sequential Detection Method for Balancing Performance Indicators of IDS, The 7th International Symposium on Computing and Networking, CANDAR 2019, 10.1109/CANDAR.2019.00039, 239-244, 2019.11. |
| 12. |
Yan Naung Soe, Yaokai Feng, Paulus Insap Santosa,
Rudy Hartanto, Kouichi Sakurai, A Sequential Scheme for Detecting Cyber Attacks in IoT Enviornment, The 4th IEEE CyberSciTech2019, August 2019, 10.1109/DASC/PiCom/CBDCom/ CyberSciTech.2019.00051, 238-244, 2019.08. |
| 13. |
Yan Naung Soe, Yaokai Feng, Paulus Insap Santosa,
Rudy Hartanto, Kouichi Sakurai, Rule Generation for Signature Based Detection Systems of Cyber Attacks for IoT Environments, The Symposium MiniCandar 2019 , 2019.06. |
| 14. |
Yan Naung Soe, Yaokai Feng, Paulus Insap Santosa,
Rudy Hartanto, Kouichi Sakurai, Implementing Lightweight IoT-IDS on Raspberry Pi Using Correlation-based Feature Selection and Its Performance Evaluation, The 33rd International Conference on Advanced Information Networking and Applications (AINA-2019) , 2019.03. |
| 15. |
Ryousuke Komiya, Yaokai Feng, Kouichi Sakurai,, Detecting Distributed Cyber Attacks in SDN Based on Automatic Thresholding, The 5th International Symposium on Computing and Networking, CANDAR 2018, 2018.11. |
| 16. |
Yaokai Feng, Komiya,Kouichi Sakurai, Detecting Distributed Attacks in SDN Enviornment Based on Automatic Thresholding, 6th International Workshop on Cyber Security Workshop on IoT Security: Smart Secure homes, 2018.09. |
| 17. |
Yaokai Feng, Hitoshi Akiyama,Liang Lu,Kouichi, Sakurai, Feature Selection For Machine Learning-Based Early Detection of Distributed Cyber-Attacks, The 4th IEEE Cyber Science and Technology Conference, 173-180, 2018.08. |
| 18. |
Jiawei Su, Danilo Vasconcellos Vargas, Sanjiva Prasad, Daniele Sgandurra, Yaokai Feng, Kouichi Sakurai:, Lightweight Classification of IoT Malware Based on Image Recognition, The 42nd IEEE International Conference COMPSAC (2) 2018, 664-669, 2018.07. |
| 19. |
Yaokai Feng, Yoshiaki Hori, Kouichi Sakurai, Detecting DDoS Attacks Based Using Normal Modes, The 10th Workshop among Asian Information Security Labs (WAIS 2018), 2018.01, 2018.01. |
| 20. |
Yaokai Feng, Yoshiaki Hori, Kouichi Sakurai, A Detection System for Distributed DoS Attacks Based on Automatic Extraction of Normal Mode and Its Performance Evaluation, the 10th International Conference on Security, Privacy and Anonymity (SpaCCS2017) LNCS 10656, 2017.12, 2017.12. |
| 21. |
Xiang You, Yaokai Feng, Kouichi Sakurai, Packet In message based DDoS attack detection in SDN network using OpenFlow, The 4th International Symposium on Computing and Networking, CANDAR 2017, 522-528, 2017.11. |
| 22. |
Liang Lv, Yaokai Feng, Kouichi Sakurai, Detecting C&C Sessions of Cyber Attacks using Random Forest, The 11th International Conference on Ubiquitous Information Management and Communication, 2017.01. |
| 23. |
Ziyi Li, Junpei Kawamoto, Yaokai Feng, Kouichi Sakurai, Cyberbullying detection using parent-child relationship between comments, The 18th International Conf. on Information Integration and Web-based Applications and Services, 2016.11. |
| 24. |
Yuxuan Gao, Yaokai Feng, Junpei Kawamoto, Kouichi Sakurai, A Machine Learning Based Approach for Detecting DRDoS Attacks and Its Performance Evaluation, the 11th Asia Conference on information security, IEEE CPS,, DOI 10.1109/AsiaJCIS.2015.22, 2016.08, DRDoS (Distributed Reflection Denial of Service) attack is a kind of DoS (Denial of Service) attack, in which third-party servers are tricked into sending large amounts of data to the victims.. |
| 25. |
Yaokai Feng, Yoshiaki Hori, Kouichi Sakurai, A Behavior-based Online Engine for Detecting Distributed Cyber Attacks, the 17th World Conference on Information Security Applications,, 2016.08. |
| 26. |
Longzhu Cai, Yaokai Feng, Junpei Kawamoto, Kouichi Sakurai, A Behavior-based Method for Detecting DNS Amplification Attacks, The 10-th International Workshop on Advances in Information Security, 2016.07. |
| 27. |
Pengfei Li, Yaokai Feng, Junpei Kawamoto, Kouichi Sakurai, A Proposal for Cyber-Attack Trace-back Using Packet Marking and Logging, The 10-th International Workshop on Advances in Information Security, 2016.07. |
| 28. |
Yaokai Feng, How to fight against Botnets in IoT, The 3rd International Workshop on Cybersecurity, 2016.01. |
| 29. |
Yaokai Feng, Yoshiaki Hori, Kouichi Sakurai, A Proposal for Detecting Distributed Cyber-Attacks Using Automatic Thresholding, the 10th Asia Conference on information security, IEEE CPS, DOI 10.1109/AsiaJCIS.2015.22, 152-159, 2015.05. |
| 30. |
Can Wang, Yaokai Feng, Junpei Kawamoto, Yoshiaki Hori, Kouichi Sakurai,
A Parameterless Learning Algorithm for Behavior-Based Attack Detection, 9th Asia Conference on information security, 2014.09. |
| 31. |
Kohei Inai, Marten Palsson, FRINKEN VOLKMAR, Yaokai Feng, Seiichi Uchida, Selective Concealment of Characters for Privacy Protection, the 22nd International Conference on Pattern Recognition, Poster, 2014.08. |
| 32. |
Kohei Inai, Marten Palsson, Volkmar Frinken, Yaokai Feng, Seiichi Uchida, Selective Concealment of Characters for Privacy Protection, Proceedings of the 22nd International Conference on Pattern Recognition (ICPR2014), 2014.08. |
| 33. |
Yoshiaki Hori, Yaokai Feng, Akira Nagata, Kohei Kotera, Katsuichi Nakamura, Traffic Anomaly Detection supporting M2M devices, The 9th ACM Symposium on Information, Computer and Communications Security (ASIACCS 2014), Poster, 2014.06. |
| 34. |
Kensho Fujisaki, Ayumi Hamano, Kenta Aoki, Yaokai Feng, Seiichi Uchida, Detection and Tracking Protein Molecules in Fluorescence Microscopic Video, Proceedings of The 1st International Workshop on BioImage Recognition (BIR'131), 2013.12. |
| 35. |
Rong Huang, Palaiahnakote Shivakumara, Yaokai Feng, Seiichi Uchida, Scene Character Detection and Recognition with Cooperative Multiple-Hypothesis Framework,
IEICE Transactions on Information & Systems, 10.1587/transinf.E96.D.2235, Vol.E96-D, No.10, Page 2235-2244 , 2013.10. |
| 36. |
Koichi Ogawara, Masahiro Fukutomi, Seiichi Uchida, Yaokai Feng, A Voting-Based Sequential Pattern Recognition Method, PLOS ONE , Vol.8, No.10, 2013.10. |
| 37. |
Renwu Gao, Faisal Shafait, Seiichi Uchida, Yaokai Feng, Saliency inside Saliency - A Hierarchical Usage of Visual Saliency for Scene Character Detection, Proceedings of The Fifth International Workshop on Camera-Based Document Analysis and Recognition (CBDAR2013, Washington DC, USA), 2013.08. |
| 38. |
Yugo Terada, Rong Huang, Yaokai Feng, Seiichi Uchida, On the Possibility of Structure Learning-Based Scene Character Detector, Proceedings of The 12th International Conference on Document Analysis and Recognition (ICDAR 2013, Washington DC, USA), 2013.08. |
| 39. |
Masanori Goto, Ryosuke Ishida, Yaokai Feng, Seiichi Uchida, Analyzing the Distribution of a Large-scale Character Pattern Set Using Relative Neighborhood Graph, Proceedings of The 12th International Conference on Document Analysis and Recognition (ICDAR 2013, Washington DC, USA), 2013.08. |
| 40. |
Soma Shiraishi, Yaokai Feng, Seiichi Uchida, Skew Estimation by Parts,
IEICE Transactions on Information & Systems, 10.1587/transinf.E96.D.1503, Vol.E96-D, No.7, page 1503-1512, 2013.07. |
| 41. |
Yaokai Feng, Yoshiaki Hori, Kouichi Sakurai, Jun'ichi Takeuchi,
A Behavior-Based Method for Detecting Distributed Scan Attacks in Darknets,
Journal of Information Processing, 10.22197/ipsjjip.21.527, Vol.21, No.3, page 527-538, 2013.07. |
| 42. |
Takafumi Matsuo, Song Wang, Yaokai Feng and Seiichi Uchida, Exploring the Ability of Parts on Recognizing Handwriting Characters, the 16th International Graphonomics Society Conference (IGS 2013), (Accepted), 2013.06. |
| 43. |
Song Wang, Seiichi Uchida, Marcus Liwicki, Yaokai Feng, Part-Based Methods for Handwritten Digit Recognition,
Frontiers of Computer Science , 10.1007/s11704-013-2297-x , Vol. 7, No. 4, page 514-525, 2013.03. |
| 44. |
Seiichi Uchida, Masahiro Fukutomi, Koichi Ogawara, and Yaokai Feng, Non-Markovian Dynamic Time Warping , the 21st International Conference on Pattern Recognition (ICPR2012), 2294-2297, 2012.11. |
| 45. |
Seiichi Uchida, Satoshi Hokahori, and Yaokai Feng, Analytical Dynamic Programming Matching , the Fifth Workshop on Non-Rigid Shape Analysis and Deformable Image Alignment (NORDIA'12), LNCS 7583, pp.92-101, , 92-101, 2012.09. |
| 46. |
Seiichi Uchida, Ryosuke Ishida, Akira Yoshida, Wenjie Cai and Yaokai Feng, Character Image Patterns as Big Data , the 13th International Conference on Frontiers in Handwriting Recognition (ICFHR2012), 477-482, 2012.09. |
| 47. |
Yutaro Iwakiri, Soma Shiraishi, Yaokai Feng and Seiichi Uchida, On the Possibility of Instance-Based Stroke Recovery , the 13th International Conference on Frontiers in Handwriting Recognition (ICFHR2012), 29-34, 2012.09. |
| 48. |
Yaokai Feng, Yoshiaki Hori, Kouichi Sakurai, Jun'ichi Takeuchi, A Behavior-based Detection Method for Outbreaks of Low-rate Attacks, The Third Workshop on Network Technologies for Security, Administration and Protection (Netsap in SAINT 2012)
, 267-272, 2012.07, Low-rate attacks can conceal their traffic because their packets are at very low rates, which make it easy to bury themselves into the normal traffic. Thus, although a number of volume-based detection techniques are able to identify anomalies that trigger significant changes in traffic volume, they are not applicable to detecting low-rate attacks. Because of this, the problem of low-rate attacks has been attracting many researchers in the community of network security. In this study, for the first time we propose a method based on the normal behavior mode of traffic to detect outbreaks of low-rate attacks. The experimental result indicates that our proposal is efficient.. |
| 49. |
Soma Shiraishi, Yaokai Feng and Seiichi Uchida
, A Part-Based Skew Estimation Method
, The 10th IAPR International Workshop on Document Analysis Systems (DAS2012, Gold Coast, Australia)
, 185-189, 2012.03. |
| 50. |
Soma Shiraishi, Yaokai Feng, Seiichi Uchida, Part-Based Skew Estimation for Mathematical Expressions
, The International Workshop on Digitization and E-Inclusion in Mathematics and Science 2012 (DEIMS12, Tokyo, Japan)
, 33-41, 2012.02. |
| 51. |
Kenta AOKI, Kensho FUJISAKI, Yaokai FENG, Seiichi UCHIDA, Detection and Tracking of Particles in Cell
, The 7th Joint Workshop on Machine Perception and Robotics, 2011.10. |
| 52. |
Soma SHIRAISHI, Yaokai FENG, Seiichi UCHIDA, Skew Correction by Majority Voting
, The 7th Joint Workshop on Machine Perception and Robotics, 2011.10. |
| 53. |
Seiichi Uchida, Toru Sasaki and Yaokai Feng
, A Generative Model for Handwritings Based on Enhanced Feature Desynchronization
, Proc. the 10th International Conference on Document Analysis and Recognition (ICDAR 2011), 2011.09. |
| 54. |
Yasuhiro Kunishige, Yaokai Feng and Seiichi Uchida
, Scenery Character Detection with Environmental Context
, Proc. the 10th International Conference on Document Analysis and Recognition (ICDAR 2011), 2011.09. |
| 55. |
Seiichi Uchida, Yuki Shigeyoshi, Yasuhiro Kunishige and Yaokai Feng
, A Keypoint-Based Approach Toward Scenery Character Detection
, Proc. the 10th International Conference on Document Analysis and Recognition (ICDAR 2011), 2011.09. |
| 56. |
Yaokai Feng, Akifumi Makinouchi, Ag+-tree: an Index Structure for Range-aggregation Queries in Data Warehouse Environments, International Journal of Database Theory and Application, Vol. 4, No. 2, page 51-64, 2011.08. |
| 57. |
Yaokai Feng, Akifumi Makinouchi, A New Structure for Accelerating Xpath Location Steps,
International Journal of Computer Science, Vol.38, No.2, page 113-121, 2011.06. |
| 58. |
Yaokai Feng, kunihiko kaneko, Akifumi Makinouchi, Efficient Evaluation of Partially-dimensional Range Queries in Large OLAP Datasets,
International Journal of Data Mining, Modelling and Management, DOI: 10.1504/IJDMMM.2011.041493, Vol.3, No.2, page 150-171, 2011.06. |
| 59. |
Wenjie Cai, Yaokai Feng and Seiichi Uchida , Massive Character Recognition with a Large Ground-Truthed Database, The 26th ACM Symposium on Applied Computing, 2011.03. |
| 60. |
Yaokai Feng, Seiichi Uchida, (invited paper) Are kansei Database Systems Possible?, Proceedings of ICMSIE , 123-128, 2010.12. |
| 61. |
Seiichi Uchida, Ikko Fujimura, Hiroki Kawano, Yaokai Feng , Analytical dynamic programming tracker
, The 10th Asian Conference on Computer Vision (ACCV), Lecture Notes in Computer Science, 2011, Volume 6492/2011, Springer, 296-309, 2010.11. |
| 62. |
Yaokai Feng, Zentaro Ono, Seiji Hotta and Seiichi Uchida, To Improve Performance of Image Localization , The 2nd China-Japan-Korea Joint Workshop on Pattern Recogition (CJKPR) , 16-19, 2010.11. |
| 63. |
M. Fukutomi, K. Ogawara, Y. Feng, and S. Uchida, Sequential Pattern Recognition by Combining Local Classifiers, The 2nd China-Japan-Korea Joint Workshop on Pattern Recogition (CJKPR) , 209-212, 2010.11. |
| 64. |
Yaokai Feng, Zentaro Ono, and Seiichi Uchida, Using Spatial Information of the Keypoints to Improve Performance of Image Localization
, The 6th Joint Workshop on Machine Perception and Robotics, 2010.10. |
| 65. |
Yaokai Feng, Seiichi Uchida, How to Design Kansei Retrieval Systems?, The 11th International Conference on Web-Age Information Management (WAIM2010), Lecture Note on Computer Science, LNCS 6184, Springer-Verlag, , 405-416, 2010.07. |
| 66. |
Zentaro ONO, Seiji HOTTA, Yaokai FENG, and Seiichi UCHIDA, A Comparative Study on Image Localization Technologies
, Joint Workshop on Machine Perception and Robotics , 2009.10. |
| 67. |
Hiroki Kawano, Ikko Fujimura, Yaokai Feng, and Seiichi Uchida, Object Tracking using Analytical DP with Bi-Directional Strategy,Joint Workshop on Machine Perception and Robotics ,2009.10.05, Joint Workshop on Machine Perception and Robotics, 2009.10. |
| 68. |
Masahiro Fukutomi, Koichi Ogawara, Yaokai Feng, and Seiichi Uchida, Recognition of Sequential Pattern by Local Classifiers, Joint Workshop on Machine Perception and Robotics , 2009.10. |
| 69. |
Yaokai Feng, Kunihiko Kaneko, Prefix Similarity Search in Time Series Databases and a Scheme for its Efficient Evaluation, The 12th International Conference on Systemics and Informatics, 2008.07. |
| 70. |
Yaokai Feng, To Reveal the Performance secrets of Nearest Neighbor Searching,
International Journal of Software Engineering and Its Applications (SELECTED from International Conference IPC 2007), Vol.2, No. 1, page 55-72, 2008.01. |
| 71. |
Yaokai Feng, Akifumi Makinouchi, kunihiko kaneko, An Estimating Model of Node Accesses for INN Search Algorithm in Multidimensional Spaces , Engineering Letters , Vol. 15 No.2 page 184-192, 2007.12. |
| 72. |
Yaokai Feng, Akifumi Makinouchi, Kunihiko Kaneko, Proposals to Improve Query Performance on Business Data, International Journal of Computer Science , Vol. 34 No.2, Pages 199-206, 2007.12. |
| 73. |
Yaokai Feng, Akifumi Makinouchi, Kunihiko Kaneko, A Cost Model for Incremental Nearest Neighbor Search in Multidimensional Spaces., The 2007 International Conference on Intelligent Computing, IEEE CS press (SELECTED for journal publication), 2007.10. |
| 74. |
Yaokai Feng, Kunihiko Kaneko and Akifumi Makinouchi, Sorting AR*-tree: Further Improving the Performance of Partially-dimensional Range Queries, IEEE International Conference PACRIM2007 , Page 375-378, 2007.08. |
| 75. |
Yaokai Feng, Akifumi Makinouchi, Efficient Evaluation of Partially-dimensional Range Queries Using Adaptive R*-tree, 17th International Conference on Database and Expert Systems Applications (DEXA 2006),, LNCS 4080, pp. 687-696, Springer-Verlag, (Acceptance Rate: 23%), 2006.09. |
| 76. |
Yaokai Feng, Akifumi Makinouchi, A New Structure for Accelerating XPath Location Steps, The Seventh International Conference on Web-Age Information Management(WAIM), LNCS 4016, pp. 49-60, Springer-Verlag, (Acceptance Rate: 17%), 2006.06. |
| 77. |
Yaokai Feng, Akifumi Makinouchi, Ag-Tree: A Novel Structure for Range Queries in Datawarehouse Environments, Proc. the 11th International Conference on Database Systems for Adavanced Applications (DASFAA),, LNCS 3882, pp. 498-512, Springer-Verlag, (Acceptance Rate: 25%), 2006.04. |
| 78. |
Yaokai Feng, Akifumi Makinouchi, A Hybrid Clustering Criterion for R*-tree on Business Data, Proc. the 7th International Conference on Enterprise Information Systems(ICEIS), ISBN: 972-8865-19-8, pp.346-352, 2005.05. |
| 79. |
Yaokai Feng, Zhibin Wang, Akifumi Makinouchi, Towards Range Queries in OLAP Applications, Proc. IPSJ Database Workshop (DBWS2004),
IPSJ SIG Technical Report, Vol.2004, Vol.71, pp.31-37, 2004.07. |
| 80. |
Yaokai Feng, Zhibin Wang, Akifumi Makinouchi, Towards QPD: Queries with Partial Dimensions, IEICE Technical Report,
, Vol.104, No.176, pp.25-30, 2004.07. |
| 81. |
Yaokai Feng, Akifumi Makinouchi and Hiroshi Ryu, Improving Query Performance on OLAP-Data Using Enhanced
Multidimensional Indices, Proc. the 6th International Conference on Enterprise Information Systems (ICEIS2004), ISBN: 972-8865-00-7, pp.282-289, 2004.04. |
| 82. |
Yaokai Feng, Hiroshi Ryu, Akifumi Makinouch,, A Solution to “0-Area Nodes” Problems of Multidimensional Indices Used
for Business Data, Proc. International Symposium on Information Science and Electrical Engineering,, pp.283-286, 2003.11. |
| 83. |
Yaokai Feng, Akifumi Makinouchi, Batch-Incremental Nearest Neighbor Search Algorithm and Its Performance Evaluation,
IEICE Transaction on Information and Systems, E86-D, 9, 1856-1867, 2003.09. |
| 84. |
Yaokai Feng, Akifumi Makinouchi,, An Estimating Model for the Length of the Priority Queue in INN
Search, Research Reports on Information Science and Electrical Engineering of Kyushu University,, Vol.8, No.1, pp.1-6, 2003.03. |
| 85. |
Yaokai Feng, Akifumi Makinouchi, Clustered R-trees: Improving R-trees for Nearest Neighbor Search, Proc. IASTED International Conference on Information Systems and
Databases, ISBN: 0-88986-362-8, ACTA Press, pp.7-12, 2002.09. |
| 86. |
Yaokai Feng, Akifumi Makinouchi, An Estimating Model for the Number of Node Accesses in NN Search, Research Reports on Information Science and Electrical Engineering of Kyushu University,, Vol.7, No.2, pp.87-92, 2002.09. |
| 87. |
Yaokai Feng, Akifumi Makinouchi, A Proposal of Introducing Clustering Technology to R*-tree, Research Reports on Information Science and Electrical Engineering of Kyushu University,, Vol.7, No.2, pp.81-96,, 2002.09. |
| 88. |
Zaher Aghbari, Kun-Seok Oh, Yaokai Feng, and Akifumi Makinouchi, SOM-based k-Nearest Neighbor Search in Large Image Databases, Proc. the 6th IFIP Working Conference on Visual Database Systems (VDB6)，, pp.52-65, 2002.07. |
| 89. |
Yaokai Feng, Masaaki Kubo, Zaher Aghbari, Akifumi Makinouchi, A Proposal of Index for High-dimensional Static Databases, Proc. International Workshop on Informatics and Electrical Engineering,, pp.47-52,, 2002.05. |
| 90. |
Yaokai Feng, Akifumi Makinouchi, A New Kind of Search: k-d-NN Search and its Applications, Proc. International Workshop on Information Technologies for Network Era,, pp.313-320, 2002.03. |
| 91. |
Yaokai Feng, Akifumi Makinouchi, Performance of Incremental NN Search in R-trees, Symposium on Database and Web Information System, pp.289-296, 2001.12. |
| 92. |
Kun-Seok Oh, Yaokai Feng, Kunhiko Kaneko, and Akifumi Makinouchi, SOM-Based R*-tree for Similarity Retrieval, Proc. the 7th International Conference on Database Systems for Advanced
Applications (DASFAA),, 182-189, pp.18-189, 2001.09. |
| 93. |
Yaokai Feng, Masaaki Kubo, Akifumi Makinouchi, NSBR*-tree: Building and Retriving, Proc. IPSJ workshop DBWS2001,
(日本情報処理学会データベースシステム研究会ワークショップ), pp.207-217, 2001.07. |
