An Efficient RF power harvester for low input power with reduced dead-zone
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: 2014DOI: 10.1109/IGARSS.2014.6946717
Keyword(s): feature extraction,geophysical image processing,geophysical techniques,image classification,adaptive high resolution land classification,global HR-VHR image information extraction,high resolution imagery,information extraction process,interscale classification,interscale learning paradigm,traditional machine learning techniques,Data mining,Feature extraction,Information retrieval,Remote sensing,Spatial resolution,Training
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An Efficient RF power harvester for low input power with reduced dead-zone
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| date accessioned | 2020-03-12T20:21:36Z | |
| date available | 2020-03-12T20:21:36Z | |
| date issued | 2014 | |
| identifier other | 6865465.pdf | |
| identifier uri | https://libsearch.um.ac.ir:443/fum/handle/fum/1011636 | |
| format | general | |
| language | English | |
| publisher | IEEE | |
| title | An Efficient RF power harvester for low input power with reduced dead-zone | |
| type | Conference Paper | |
| contenttype | Metadata Only | |
| identifier padid | 8134222 | |
| subject keywords | feature extraction | |
| subject keywords | geophysical image processing | |
| subject keywords | geophysical techniques | |
| subject keywords | image classification | |
| subject keywords | adaptive high resolution land classification | |
| subject keywords | global HR-VHR image information extraction | |
| subject keywords | high resolution imagery | |
| subject keywords | information extraction process | |
| subject keywords | interscale classification | |
| subject keywords | interscale learning paradigm | |
| subject keywords | traditional machine learning techniques | |
| subject keywords | Data mining | |
| subject keywords | Feature extraction | |
| subject keywords | Information retrieval | |
| subject keywords | Remote sensing | |
| subject keywords | Spatial resolution | |
| subject keywords | Training | |
| identifier doi | 10.1109/IGARSS.2014.6946717 | |
| journal title | ircuits and Systems (ISCAS), 2014 IEEE International Symposium on | |
| filesize | 536133 | |
| citations | 0 | |
| contributor rawauthor | Goncalves, H. , Fernandes, J. , Rabuske, T. , Martins, M. |