Energy-aware current-mode inter-chip link for a dependable GALS NoC platform
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: 2014DOI: 10.1109/IGARSS.2014.6946719
Keyword(s): agriculture,backscatter,crops,feature extraction,geophysical image processing,image classification,image texture,maximum likelihood estimation,radar imaging,synthetic aperture radar,vegetation mapping,Lombardy region,SAR multitemporal features,SAR multitemporal seasonal data,agricultural area,agricultural crop mapping,agricultural practices,backscatter features,backscatter temporal trend,classification approach,corn,ground-measured data,information extraction,maximum likel
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Energy-aware current-mode inter-chip link for a dependable GALS NoC platform
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| date accessioned | 2020-03-12T20:21:42Z | |
| date available | 2020-03-12T20:21:42Z | |
| date issued | 2014 | |
| identifier other | 6865522.pdf | |
| identifier uri | https://libsearch.um.ac.ir:443/fum/handle/fum/1011692?locale-attribute=en | |
| format | general | |
| language | English | |
| publisher | IEEE | |
| title | Energy-aware current-mode inter-chip link for a dependable GALS NoC platform | |
| type | Conference Paper | |
| contenttype | Metadata Only | |
| identifier padid | 8134296 | |
| subject keywords | agriculture | |
| subject keywords | backscatter | |
| subject keywords | crops | |
| subject keywords | feature extraction | |
| subject keywords | geophysical image processing | |
| subject keywords | image classification | |
| subject keywords | image texture | |
| subject keywords | maximum likelihood estimation | |
| subject keywords | radar imaging | |
| subject keywords | synthetic aperture radar | |
| subject keywords | vegetation mapping | |
| subject keywords | Lombardy region | |
| subject keywords | SAR multitemporal features | |
| subject keywords | SAR multitemporal seasonal data | |
| subject keywords | agricultural area | |
| subject keywords | agricultural crop mapping | |
| subject keywords | agricultural practices | |
| subject keywords | backscatter features | |
| subject keywords | backscatter temporal trend | |
| subject keywords | classification approach | |
| subject keywords | corn | |
| subject keywords | ground-measured data | |
| subject keywords | information extraction | |
| subject keywords | maximum likel | |
| identifier doi | 10.1109/IGARSS.2014.6946719 | |
| journal title | ircuits and Systems (ISCAS), 2014 IEEE International Symposium on | |
| filesize | 1981981 | |
| citations | 0 | |
| contributor rawauthor | Shirahama, H. , Mochizuki, A. , Watanabe, Y. , Hanyu, T. |