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Surround Inhibition Mechanism by Deep Learning
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- SUGAMOTO Mamoru
- apprhythm inc.
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- FUJIMOTO Naoaki
- Tama Art U.
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- ONOUE Muneharu
- Geelive, Inc
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- YUMIBAYASHI Tsukasa
- Otsuma Women’s U.
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- SUGAMOTO Akio
- Ochanomizu U. and OUJ
Description
<p>In the sensation of tones, visions and other stimuli, the “surround inhibition mechanism” (or “lateral inhibition mechanism”) is crucial. The mechanism enhances the signals of the strongest tone, color and other stimuli, by reducing and inhibiting the surrounding signals, since the latter signals are less important. This surround inhibition mechanism is well studied in the physiology of sensor systems. The neural network with two hidden layers in addition to input and output layers is constructed; having 60 neurons (units) in each of the four layers. The label (correct answer) is prepared from an input signal by applying seven times operations of the “Hartline mechanism”, that is, by sending inhibitory signals from the neighboring neurons and amplifying all the signals afterwards. The implication obtained by the deep learning of this neural network is compared with the standard physiological understanding of the surround inhibition mechanism.</p>
Journal
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- Proceedings of the Annual Conference of JSAI
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Proceedings of the Annual Conference of JSAI JSAI2019 (0), 2H3J201-2H3J201, 2019
The Japanese Society for Artificial Intelligence
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Keywords
Details 詳細情報について
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- CRID
- 1390001288143392384
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- NII Article ID
- 130007658475
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- ISSN
- 27587347
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- Text Lang
- ja
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- Data Source
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- JaLC
- CiNii Articles
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- Abstract License Flag
- Disallowed