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Biologically inspired deep learning system applied to Egyption multi-style license plate detection / Amr Abdellatief Abdelaal ; Supervised Elsayed E. Hemayed

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Amr Abdellatief Abdelaal , 2018Description: 45 P. : chartas , facsimiles , photoghraphs ; 30cmOther title:
  • نظام يحاكي نظم الرؤيه الطبيعيه مبني علي التعلم المتعمق لاكتشاف لوحات ترخيص السيارات المصرية [Added title page title]
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Dissertation note: Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Computer Engineering Summary: This thesis presents a proposed biologically inspired deep learning system and performance on two tasks: first task is detection of Egyptian Car license plates. The second task is general object detection task in which we used the System to detect different objects in the Graz-02 object detection Dataset. the system consists of two main parts or stages: the first stage role is finding candidate object areas in the image. The second stage is mainly responsible for detecting precisely the objects among the candidate areas which are output from the previous stage. The system achieved detection percentage of 95% in detection of car plates task. In addition to this task we applied our proposed system to general object detection from the Graz-02 data set. It has different types of categories (Car, Bike and people). We achieved average percent of 75% on all those categories
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Item type Current library Home library Call number Copy number Status Date due Barcode
Thesis Thesis قاعة الرسائل الجامعية - الدور الاول المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.06.M.Sc.2018.Am.B (Browse shelf(Opens below)) Not for loan 01010110077594000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.06.M.Sc.2018.Am.B (Browse shelf(Opens below)) 77594.CD Not for loan 01020110077594000

Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Computer Engineering

This thesis presents a proposed biologically inspired deep learning system and performance on two tasks: first task is detection of Egyptian Car license plates. The second task is general object detection task in which we used the System to detect different objects in the Graz-02 object detection Dataset. the system consists of two main parts or stages: the first stage role is finding candidate object areas in the image. The second stage is mainly responsible for detecting precisely the objects among the candidate areas which are output from the previous stage. The system achieved detection percentage of 95% in detection of car plates task. In addition to this task we applied our proposed system to general object detection from the Graz-02 data set. It has different types of categories (Car, Bike and people). We achieved average percent of 75% on all those categories

Issued also as CD

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