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Committee Date Time Place Paper Title / Authors Abstract Paper #
IBISML 2014-11-18
Aichi Nagoya Univ. [Poster Presentation] Performance analysis of auto-associative neural networks on diluted modular networks
Toshiyuki Yamane (TRL), Gouhei Tanaka (Univ. Tokyo), Daiju Nakano (TRL), Ryosho Nakane (Univ. Tokyo), Yasunao Katayama (TRL) IBISML2014-82
We report the performance analysis of auto-associative neural networks on modular structures.
We focus on the sparse mo... [more]
Tokyo Tamagawa University A method to improve the performance of auto-associative memory for face recognition
Hiroshi Kage (Mitsubishi Electric) NC2013-101
The recent increase of surveillance cameras installed in public spaces is evoking a strong demand for face recognition s... [more] NC2013-101
Tokyo Tamagawa University Recalling reversal and spread-out spike patterns can be realized in a recurrent network.
Keita Sato, Ryota Miyata, Toru Aonishi (Tokyo Inst. of Tech.) NC2013-104
Recent experimental findings suggest that the hippocampal network including CA1 and CA3 regions stores spatio-temporal s... [more] NC2013-104
NC, IPSJ-BIO 2013-06-28
Okinawa Okinawa Institute of Science and Technology Optimal pairs of coupling function and STDP window function for auto-associative memory
Ryota Miyata, Keita Sato, Toru Aonishi (Tokyo Inst. of Tech.) NC2013-6
From the computational viewpoint, Lengyel et al. (2005) derived an optimal auto-associative memory algorithm to store an... [more] NC2013-6
NC 2006-06-16
Okinawa OIST Performance estimation of face authentication based on auto-associative memory
Hiroshi Kage, Shitaro Watanabe, Ken-ichi Tanaka, Kazuo Kyuma (Mitsbubishi Electric Corp.)
In some situations of face authentication by face images, the system performance will be degraded caused by partial occl... [more] NC2006-30
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