Ge and GaAs integration for device applications
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: 2014DOI: 10.1109/CIEC.2014.6959075
Keyword(s): Accuracy,Diseases,Electrooculography,Instruments,Kernel,Polynomials,Support vector machines,Autoregressive Parameters(AR),Blink Detection,Electrooculogram (EOG),Eye Dystonia,Hjorth Parameters,Power Spectral Density (PSD),Support Vector Machine (SVM)
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Ge and GaAs integration for device applications
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| date accessioned | 2020-03-12T20:30:20Z | |
| date available | 2020-03-12T20:30:20Z | |
| date issued | 2014 | |
| identifier other | 6874693.pdf | |
| identifier uri | http://libsearch.um.ac.ir:80/fum/handle/fum/1016802?locale-attribute=en | |
| format | general | |
| language | English | |
| publisher | IEEE | |
| title | Ge and GaAs integration for device applications | |
| type | Conference Paper | |
| contenttype | Metadata Only | |
| identifier padid | 8140733 | |
| subject keywords | Accuracy | |
| subject keywords | Diseases | |
| subject keywords | Electrooculography | |
| subject keywords | Instruments | |
| subject keywords | Kernel | |
| subject keywords | Polynomials | |
| subject keywords | Support vector machines | |
| subject keywords | Autoregressive Parameters(AR) | |
| subject keywords | Blink Detection | |
| subject keywords | Electrooculogram (EOG) | |
| subject keywords | Eye Dystonia | |
| subject keywords | Hjorth Parameters | |
| subject keywords | Power Spectral Density (PSD) | |
| subject keywords | Support Vector Machine (SVM) | |
| identifier doi | 10.1109/CIEC.2014.6959075 | |
| journal title | ilicon-Germanium Technology and Device Meeting (ISTDM), 2014 7th International | |
| filesize | 2781236 | |
| citations | 0 | |
| contributor rawauthor | Ching-Kean Chia , Iskander, A. , Yuanbing Cheng , Jin Yunjiang , Dalapati, G.K. , Qiuwei, T.Z. |