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» Computational model for amygdala neural networks
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ASAP
2009
IEEE
182views Hardware» more  ASAP 2009»
15 years 11 months ago
NeMo: A Platform for Neural Modelling of Spiking Neurons Using GPUs
—Simulating spiking neural networks is of great interest to scientists wanting to model the functioning of the brain. However, large-scale models are expensive to simulate due to...
Andreas Fidjeland, Etienne B. Roesch, Murray Shana...
IJON
2006
91views more  IJON 2006»
15 years 1 months ago
Symmetry axis extraction by a neural network
This paper proposes a neural network model that extracts axes of symmetry from visual patterns. The input patterns can be line drawings, plane figures or gray-scaled natural image...
Kunihiko Fukushima, Masayuki Kikuchi
ICRA
2009
IEEE
137views Robotics» more  ICRA 2009»
15 years 8 months ago
Continuous vocal imitation with self-organized vowel spaces in Recurrent Neural Network
Abstract— A continuous vocal imitation system was developed using a computational model that explains the process of phoneme acquisition by infants. Human infants perceive speech...
Hisashi Kanda, Tetsuya Ogata, Toru Takahashi, Kazu...
IROS
2008
IEEE
161views Robotics» more  IROS 2008»
15 years 8 months ago
Segmenting acoustic signal with articulatory movement using Recurrent Neural Network for phoneme acquisition
— This paper proposes a computational model for phoneme acquisition by infants. Human infants perceive speech sounds not as discrete phoneme sequences but as continuous acoustic ...
Hisashi Kanda, Tetsuya Ogata, Kazunori Komatani, H...
WAPCV
2004
Springer
15 years 7 months ago
Learning of Position-Invariant Object Representation Across Attention Shifts
Abstract. Selective attention shift can help neural networks learn invariance. We describe a method that can produce a network with invariance to changes in visual input caused by ...
Muhua Li, James J. Clark