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Fingerprint Fingerprint is based on mining the text of the person's scientific documents to create an index of weighted terms, which defines the key subjects of each individual researcher.

  • 6 Similar Profiles
Neural networks Engineering & Materials Science
Nonlinear systems Engineering & Materials Science
Network Programming Mathematics
Reinforcement learning Engineering & Materials Science
Support vector machines Engineering & Materials Science
Genetic Network Mathematics
Association rules Engineering & Materials Science
Evolutionary algorithms Engineering & Materials Science

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Research Output 1985 2019

  • 2157 Citations
  • 19 h-Index
  • 222 Conference contribution
  • 110 Article
  • 1 Conference article

A Convolutional Auto-Encoder Method for Anomaly Detection on System Logs

Cui, Y., Sun, Y., Furuzuki, T. & Sheng, G., 2019 Jan 16, Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018. Institute of Electrical and Electronics Engineers Inc., p. 3057-3062 6 p. 8616515. (Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Support vector machines
Ant colony optimization
Macros
Learning systems
Genes

A Metric Learning Method for Improving Neural Network Based Kernel Learning for SVM

Liang, P., Yao, X. & Furuzuki, T., 2019 Jan 16, Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018. Institute of Electrical and Electronics Engineers Inc., p. 1641-1646 6 p. 8616280. (Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Distance Education
Learning
Neural networks
Linear networks
Classifiers

Feature Extraction Using a Mutually-Competitive Autoencoder for Protein Function Prediction

Miranda, L. J. & Furuzuki, T., 2019 Jan 16, Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018. Institute of Electrical and Electronics Engineers Inc., p. 1337-1342 6 p. 8616230. (Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Feature extraction
Proteins
Neurons
Benchmarking
Statistical tests

One-Class Classification Using Quasi-Linear Support Vector Machine

Liang, P., Li, W., Wang, Y. & Furuzuki, T., 2019 Jan 16, Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018. Institute of Electrical and Electronics Engineers Inc., p. 662-667 6 p. 8616117. (Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Support vector machines
Linear networks
Classifiers
Support Vector Machine
Support vector machine

Acceleration of a CUDA-based hybrid genetic algorithm and its application to a flexible flow shop scheduling problem

Luo, J., Baz, D. E. & Furuzuki, T., 2018 Aug 20, Proceedings - 2018 IEEE/ACIS 19th International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2018. Hwang, H. J., Cai, L., Yeom, G. H., Matsuo, T., Kim, H. K., Yeo, H., Hong, C. S., Fukuta, N., Ito, T. & Miao, H. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 117-122 6 p. 8441112

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Hybrid Genetic Algorithm
Flow Shop Scheduling
Scheduling Problem
Genetic algorithms
Scheduling