Laboratory testing on a nonredundant NF-FF transformation with plane-polar scanning optimized for quasi-planar antennas
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Year
: 2014DOI: 10.1109/ICSC.2014.18
Keyword(s): learning (artificial intelligence),n pattern classification,n query processing,n support vector machines,n text analysis,n QuIET technique,n active learning approach,n annotated documents,n automatically generated span queries,n noisy local businesses data,n support vector machines,n text binary classification,n text categorization,n text classification technique,n Arrays,n Business,n Feature extraction,n Measurement,n Support vector machines
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Laboratory testing on a nonredundant NF-FF transformation with plane-polar scanning optimized for quasi-planar antennas
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| date accessioned | 2020-03-12T22:19:47Z | |
| date available | 2020-03-12T22:19:47Z | |
| date issued | 2014 | |
| identifier other | 7003367.pdf | |
| identifier uri | http://libsearch.um.ac.ir:80/fum/handle/fum/1079246?locale-attribute=en | |
| format | general | |
| language | English | |
| publisher | IEEE | |
| title | Laboratory testing on a nonredundant NF-FF transformation with plane-polar scanning optimized for quasi-planar antennas | |
| type | Conference Paper | |
| contenttype | Metadata Only | |
| identifier padid | 8215586 | |
| subject keywords | learning (artificial intelligence) | |
| subject keywords | n pattern classification | |
| subject keywords | n query processing | |
| subject keywords | n support vector machines | |
| subject keywords | n text analysis | |
| subject keywords | n QuIET technique | |
| subject keywords | n active learning approach | |
| subject keywords | n annotated documents | |
| subject keywords | n automatically generated span queries | |
| subject keywords | n noisy local businesses data | |
| subject keywords | n support vector machines | |
| subject keywords | n text binary classification | |
| subject keywords | n text categorization | |
| subject keywords | n text classification technique | |
| subject keywords | n Arrays | |
| subject keywords | n Business | |
| subject keywords | n Feature extraction | |
| subject keywords | n Measurement | |
| subject keywords | n Support vector machines | |
| identifier doi | 10.1109/ICSC.2014.18 | |
| journal title | ntenna Measurements & Applications (CAMA), 2014 IEEE Conference on | |
| filesize | 903999 | |
| citations | 0 |