| 000 | 01745cam a2200337 a 4500 | ||
|---|---|---|---|
| 003 | EG-GiCUC | ||
| 005 | 20250223031831.0 | ||
| 008 | 171026s2016 ua dh f m 000 0 eng d | ||
| 040 |
_aEG-GiCUC _beng _cEG-GiCUC |
||
| 041 | 0 | _aeng | |
| 049 | _aDeposite | ||
| 097 | _aM.Sc | ||
| 099 | _aCai01.13.08.M.Sc.2016.Ha.N | ||
| 100 | 0 | _aHany Ahmed Sayed Mansour | |
| 245 | 1 | 0 |
_aNovel techniques for enhancing automatic arabic handwriting recognition / _cHany Ahmed Sayed Mansour ; Supervised Mohsen A. Rashwan , Sherif Abdel Azeem Mohamed |
| 246 | 1 | 5 | _aتقنيات مبتكرة لتحسين التعرف الآلى على الكتابة العربية لخط اليد |
| 260 |
_aCairo : _bHany Ahmed Sayed Mansour , _c2016 |
||
| 300 |
_a60 P. : _bcharts , facsimiles ; _c30cm |
||
| 502 | _aThesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Electronics and Communication | ||
| 520 | _aIn this thesis, we present a novel segmentation free Arabic handwriting recognition systems based on hidden Markov model (HMM). Three main contributions are introduced: online Arabic handwriting recognition system, offline Arabic handwriting recognition system and combining the both offline and online systems. Experimental results and Comparisons with state of the art techniques shows that our proposed techniques are robust, effective and competitive | ||
| 530 | _aIssued also as CD | ||
| 653 | 4 | _aArabic | |
| 653 | 4 | _aOffline handwriting | |
| 653 | 4 | _aOnline handwriting | |
| 700 | 0 |
_aMohsen Abdelrazik Rashwan , _eSupervisor |
|
| 700 | 0 |
_aSherif Abdelazeem Mohamed , _eSupervisor |
|
| 856 | _uhttp://172.23.153.220/th.pdf | ||
| 905 |
_aEnas _eCataloger |
||
| 905 |
_aNazla _eRevisor |
||
| 942 |
_2ddc _cTH |
||
| 999 |
_c63140 _d63140 |
||