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Committee Date Time Place Paper Title / Authors Abstract Paper #
KBSE 2023-03-16
(Primary: On-site, Secondary: Online)
Traceability Management Method based on Informal/Semi-formal Hybrid Notation
Ryoji Okada, Yoshihiro Ohama, Seigo Ito (TCRDL) KBSE2022-56
For traceability management of design specification in software and system designing, methods using informal notation, o... [more] KBSE2022-56
Toyama Toyama Prefectural Univ. A Parallel Forward-Backward Propagation Learning Rule for Auto-Encoder
Yoshihiro Ohama, Takayoshi Yoshimura (Toyota CRDL) NC2017-3
Auto-encoder is known as a hourglass neural network for acquiring essential representations from multi-dimensional data ... [more] NC2017-3
HCS 2016-03-01
Ishikawa Rurikoh (Yamashiro Onsen) Passenger UX Prototypes in an IoT Embedded Vehicle -- In-vehicle Communication Mediated by "Things" Brought in --
Yoshihiro Ohama, Hiroshi Yasuda (Toyota CRDL) HCS2015-89
In modern vehicles, various sensors and actuators are connected each other over in-vehicle network. If these on-board el... [more] HCS2015-89
HIP 2014-03-19
Tokyo Tokyo Univ. A radio-controlled car based study for learning backward parking
Shogo Yamauchi, Naohiro Fukumura (Toyohashi Univ. of Tech), Yoshihiro Ohama, Hiroshi Yasuda (Toyota Central R&D Labs,Inc) HIP2013-93
Since there have been many drivers who are not good at parking backward, automotive manufacturers have developed several... [more] HIP2013-93
NC 2006-03-16
Tokyo Tamagawa University Application of a Forward-propagation Learning Rule for Adaptive Motor Control with Mixture Models
Yoshihiro Ohama, Naohiro Fukumura, Yoji Uno (Toyohashi Univ. Tech.)
We have proposed a forward-propagation learning (FPL) rule for acquiring neural inverse models. FPL can solve a credit a... [more] NC2005-145
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