| 000 | 01468cam a2200325 a 4500 | ||
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| 003 | EG-GiCUC | ||
| 005 | 20250223030239.0 | ||
| 008 | 100617s2010 ua dh f m 000 0 eng d | ||
| 040 |
_aEG-GiCUC _beng _cEG-GiCUC |
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| 041 | 0 | _aeng | |
| 049 | _aDeposite | ||
| 097 | _aM.Sc | ||
| 099 | _aCai01.13.06.M.Sc.2010.Ma.S | ||
| 100 | 0 | _aMahmoud Mohamed Zaki | |
| 245 | 1 | 0 |
_aSign language recognition using a combination of new vision based features / _cMahmoud Mohamed Zaki ; Supervised Samir I. Shaheen |
| 246 | 1 | 5 | _aالتعرف على لغة الاشارة باستخدام معالم مرئية جديدة |
| 260 |
_aCairo : _bMahmoud Mohamed Zaki , _c2010 |
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| 300 |
_a70P. : _bcharts , facsimiles ; _c30cm |
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| 502 | _aThesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Computer Engineering | ||
| 520 | _aSign languages are based on four components hand shape place of articulation hand orientation and movement . This thesis presents a novel combination of vision based features in order to enhance recognition of underlying signs . Three features are selected to be mapped to these four components | ||
| 530 | _aIssued also as CD | ||
| 653 | 4 | _aAppearance Based Features | |
| 653 | 4 | _aHand Gesture | |
| 653 | 4 | _aSign Language Recognition | |
| 700 | 0 |
_aSamir Ibrahim Shaheen, _eSupervisor |
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| 856 | _uhttp://172.23.153.220/th.pdf | ||
| 905 |
_aFatma _eCataloger |
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| 905 |
_aNazla _eRevisor |
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| 942 |
_2ddc _cTH |
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| 999 |
_c30709 _d30709 |
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