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Masaru Teranishi
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2010 – 2019
- 2019
- [c18]Masaru Teranishi, Shimpei Matsumoto, Hidetoshi Takeno:
Peculiarity Classification of Flat Finishing Motion Based on Tool Trajectory by Using Self-organizing Maps Part 2: Improvement of Clustering Performance Based on Codebook Vector Density. DCAI 2019: 116-124 - [c17]Masaru Teranishi
, Shimpei Matsumoto
Comparative Research on SOM with Torus and Sphere Topologies for Peculiarity Classification of Flat Finishing Skill Training. ICANN (3) 2019: 510-522 - [c16]Masaru Teranishi, Shimpei Matsumoto, Hidetoshi Takeno:
Peculiarity Classification of Flat Finishing Skill Training by using Torus Type Self-Organizing Maps with Cluster Maps. IIAI-AAI 2019: 775-780 - 2018
- [c15]Masaru Teranishi, Shimpei Matsumoto, Hidetoshi Takeno:
Peculiarity Classification of Flat Finishing Motion Based on Tool Trajectory by Using Self-organizing Maps. DCAI 2018: 78-85 - [c14]Yuichi Morioka, Katsufumi Inoue, Michifumi Yoshioka, Masaru Teranishi, Takashi Murayama:
Blur Restoration of Confocal Microscopy with Depth and Horizontal Dependent PSF. DCAI (Special Sessions) 2018: 167-174 - [c13]Masaru Teranishi, Shimpei Matsumoto, Hidetoshi Takeno:
Development of Flat Finishing Skill Training System Based on Personal Peculiarity Classification of Tool Trajectory. IIAI-AAI 2018: 730-734 - 2017
- [j6]Nobuto Fujimoto, Shimpei Matsumoto, Masaru Teranishi, Hidetoshi Takeno, Tatsushi Tokuyasu:
Examining efficient instructional methods for computer-aided brush coating skill training system in elementary and secondary education. Artif. Life Robotics 22(2): 265-275 (2017) - [c12]Masaru Teranishi, Shinpei Matsumoto, Nobuto Fujimoto, Hidetoshi Takeno:
Personal Peculiarity Classification of Flat Finishing Skill Training by using Torus type Self-Organizing Maps. DCAI 2017: 231-238 - [c11]Masaru Teranishi, Shinpei Matsumoto, Hidetoshi Takeno:
Flat Finishing Skill Training Software System Based on Personal Peculiarity Classification. SoMeT 2017: 65-72 - 2016
- [j5]Shimpei Matsumoto, Nobuto Fujimoto, Masaru Teranishi, Hidetoshi Takeno, Tatsushi Tokuyasu:
A brush coating skill training system for manufacturing education at Japanese elementary and junior high schools. Artif. Life Robotics 21(1): 69-78 (2016) - [j4]Masaru Teranishi:
Improved neural network tomography by initial learning with coarse reconstructed image. Neurocomputing 172: 399-404 (2016) - [c10]Masaru Teranishi, Shinpei Matsumoto, Nobuto Fujimoto, Hidetoshi Takeno:
Personal Peculiarity Classification of Flat Finishing Motion for Skill Training by Using Expanding Self-Organizing Maps. DCAI 2016: 137-145 - 2015
- [c9]Masaru Teranishi, Shinpei Matsumoto, Hidetoshi Takeno:
Personal peculiarity classification of flat finishing tool motion by using self-organizing maps for skill training. ASCC 2015: 1-5 - [c8]Isao Yamashita, Masaru Teranishi, Michifumi Yoshioka, Takashi Murayama, Yoshitaka Kimori:
Image restoration of confocal microscopy based on deconvolution algorithms for biological structure. ASCC 2015: 1-6 - 2014
- [c7]Masaru Teranishi, Keita Oka, Masahiro Aramoto:
Stable Learning for Neural Network Tomography by Using Back Projected Image. DCAI 2014: 327-334
2000 – 2009
- 2009
- [j3]Masaru Teranishi, Sigeru Omatu, Toshihisa Kosaka:
Continuous fatigue level estimation for the classification of fatigued bills based on an acoustic signal feature by a supervised SOM. Artif. Life Robotics 13(2): 547-550 (2009) - 2008
- [c6]Masaru Teranishi, Sigeru Omatu, Toshihisa Kosaka:
Fatigue Level Estimation of Bill by Using Supervised SOM Based on Feature-Selected Acoustic Energy Pattern. HIS 2008: 368-373 - [c5]Masaru Teranishi, Sigeru Omatu, Toshihisa Kosaka:
Fatigue level estimation of bill based on feature-selected acoustic energy pattern by using supervised SOM. CSTST 2008: 325-330 - 2002
- [c4]Masaru Teranishi, Sigeru Omatu, Toshihisa Kosaka:
Neuro-classification of Bill Fatigue Levels Based on Acoustic Wavelet Components. ICANN 2002: 1074-1079 - 2000
- [j2]Masaru Teranishi, Sigeru Omatu, Toshihisa Kosaka:
Neuro-Classification of Currency Fatigue Levels Based on Acoustic Cepstrum Patterns. J. Adv. Comput. Intell. Intell. Informatics 4(1): 18-23 (2000) - [c3]Masaru Teranishi, Sigeru Omatu, Toshihisa Kosaka:
Classification of Bill Fatigue Levels by Feature-Selected Acoustic Energy Pattern Using Competitive Neural Network. IJCNN (6) 2000: 249-252
1990 – 1999
- 1999
- [c2]Masaru Teranishi, Sigeru Omato, Toshihisa Kosaka:
New and used bills classification for cepstrum patterns. IJCNN 1999: 3978-3981 - 1998
- [c1]Masaru Teranishi, Sigeru Omatu, Toshihisa Kosaka:
New and Used Bills Classification Using Competitive Neural Network Based on Cepstrum Pattern. ICONIP 1998: 1172-1175 - 1991
- [j1]Minoru Fukumi, Sigeru Omatu, Masaru Teranishi:
A new neuron model "cone" with fast convergence rate and its application to pattern recognition. Syst. Comput. Jpn. 22(1): 91-98 (1991)
Coauthor Index
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