A hardware-based approach for implementing biological visual cortex-inspired image learning and recognition
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: 2014DOI: 10.1109/BMEI.2014.7002740
Keyword(s): Accuracy,Brain-computer interfaces,Electroencephalography,Forehead,Neural networks,Spectroscopy,Training,BP artificial neural network,classification of single channels fNIRS signal,forehead BCI
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A hardware-based approach for implementing biological visual cortex-inspired image learning and recognition
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| date accessioned | 2020-03-12T20:49:57Z | |
| date available | 2020-03-12T20:49:57Z | |
| date issued | 2014 | |
| identifier other | 6908586.pdf | |
| identifier uri | https://libsearch.um.ac.ir:443/fum/handle/fum/1027105?locale-attribute=en | |
| format | general | |
| language | English | |
| publisher | IEEE | |
| title | A hardware-based approach for implementing biological visual cortex-inspired image learning and recognition | |
| type | Conference Paper | |
| contenttype | Metadata Only | |
| identifier padid | 8152189 | |
| subject keywords | Accuracy | |
| subject keywords | Brain-computer interfaces | |
| subject keywords | Electroencephalography | |
| subject keywords | Forehead | |
| subject keywords | Neural networks | |
| subject keywords | Spectroscopy | |
| subject keywords | Training | |
| subject keywords | BP artificial neural network | |
| subject keywords | classification of single channels fNIRS signal | |
| subject keywords | forehead BCI | |
| identifier doi | 10.1109/BMEI.2014.7002740 | |
| journal title | ircuits and Systems (MWSCAS), 2014 IEEE 57th International Midwest Symposium on | |
| filesize | 896946 | |
| citations | 0 | |
| contributor rawauthor | Lu, Wenchao , Chen, Wenbo , Li, Yibo , Kaake, Ahmed , Jha, Rashmi |