Division for Theoretical Natural Science

Fingerprint The fingerprint is based on mining the text of the scientific documents related to the associated persons. Based on that an index of weighted terms is created, which defines the key subjects of research unit

Students Engineering & Materials Science
learning Social Sciences
Gesture recognition Engineering & Materials Science
student Social Sciences
Visualization Engineering & Materials Science
Radio frequency identification (RFID) Engineering & Materials Science
Learning systems Engineering & Materials Science
learning environment Social Sciences

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Research Output 1983 2018

2 Citations

Application of next-generation sequencing to the study of non-model insects

Wachi, N., Matsubayashi, K. & Maeto, K., Mar 1 2018, In : Entomological Science. 21, 1, p. 3-11 9 p.

Research output: Contribution to journalReview article

genome
insect
insects
organisms
computer hardware

Boosting over non-deterministic ZDDs

Fujita, T., hatano, K. & Takimoto, E., Jan 1 2018, WALCOM: Algorithms and Computation - 12th International Conference, WALCOM 2018, Proceedings. Springer Verlag, p. 195-206 12 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10755 LNCS).

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

Binary decision diagrams
Boosting
Adaptive boosting
Decision Diagrams
Learning algorithms
1 Citations

Can machine learning techniques provide better learning support for elderly people?

hatano, K., Jan 1 2018, Distributed, Ambient and Pervasive Interactions: Technologies and Contexts - 6th International Conference, DAPI 2018, Held as Part of HCI International 2018, Proceedings. Konomi, S. & Streitz, N. (eds.). Springer Verlag, p. 178-187 10 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10922 LNCS).

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

Elderly People
Learning systems
Machine Learning
Decision making
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