Fast and robust zebrafish segmentation and detection algorithm under different spectrum conditions
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: 2014DOI: 10.1109/ITEC-AP.2014.6940791
Keyword(s): Kalman filters,battery management systems,digital signal processing chips,electric vehicles,nonlinear filters,secondary cells,BMS,DSP,EKF algorithm,MATLAB simulation,SOC estimation,TMS320LF2407,Thevenin battery model,battery state of charge estimation,control chip,electric vehicle battery management system,expanded Kalman filter algorithm,lithium iron phosphate battery,Batteries,Battery management systems,Discharges (electric),Electric vehicles,Estimation,Mathematical mode
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Fast and robust zebrafish segmentation and detection algorithm under different spectrum conditions
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| date accessioned | 2020-03-12T19:39:18Z | |
| date available | 2020-03-12T19:39:18Z | |
| date issued | 2014 | |
| identifier other | 6798944.pdf | |
| identifier uri | https://libsearch.um.ac.ir:443/fum/handle/fum/985070?locale-attribute=en | |
| format | general | |
| language | English | |
| publisher | IEEE | |
| title | Fast and robust zebrafish segmentation and detection algorithm under different spectrum conditions | |
| type | Conference Paper | |
| contenttype | Metadata Only | |
| identifier padid | 8100629 | |
| subject keywords | Kalman filters | |
| subject keywords | battery management systems | |
| subject keywords | digital signal processing chips | |
| subject keywords | electric vehicles | |
| subject keywords | nonlinear filters | |
| subject keywords | secondary cells | |
| subject keywords | BMS | |
| subject keywords | DSP | |
| subject keywords | EKF algorithm | |
| subject keywords | MATLAB simulation | |
| subject keywords | SOC estimation | |
| subject keywords | TMS320LF2407 | |
| subject keywords | Thevenin battery model | |
| subject keywords | battery state of charge estimation | |
| subject keywords | control chip | |
| subject keywords | electric vehicle battery management system | |
| subject keywords | expanded Kalman filter algorithm | |
| subject keywords | lithium iron phosphate battery | |
| subject keywords | Batteries | |
| subject keywords | Battery management systems | |
| subject keywords | Discharges (electric) | |
| subject keywords | Electric vehicles | |
| subject keywords | Estimation | |
| subject keywords | Mathematical mode | |
| identifier doi | 10.1109/ITEC-AP.2014.6940791 | |
| journal title | ensors Applications Symposium (SAS), 2014 IEEE | |
| filesize | 807131 | |
| citations | 0 | |
| contributor rawauthor | Jei Shian Tan , Tak Kwin Chang , Ooi, M.P.-L. , Ye Chow Kuang , Chee Pin Tan , Kitahashi, T. |