Efeler, Mahmut Cenk

Loading...
Name Variants
Job Title
Email Address
mahmutefeler@iyte.edu.tr
Main Affiliation
03.05. Department of Electrical and Electronics Engineering
Status
Current Staff
Website
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID

Sustainable Development Goals

SDG data is not available
This researcher does not have a Scopus ID.
Documents

1

Citations

0

Scholarly Output

1

Articles

0

Views / Downloads

848/0

Supervised MSc Theses

0

Supervised PhD Theses

0

WoS Citation Count

0

Scopus Citation Count

0

Patents

0

Projects

0

WoS Citations per Publication

0.00

Scopus Citations per Publication

0.00

Open Access Source

0

Supervised Theses

0

JournalCount
2013 21st Signal Processing and Communications Applications Conference, SIU 20131
Current Page: 1 / 1

Scopus Quartile Distribution

Quartile distribution chart data is not available

Competency Cloud

GCRIS Competency Cloud

Scholarly Output Search Results

Now showing 1 - 1 of 1
  • Conference Object
    A Bayesian Approach for Licence Plate Recognition Developed on a Realistic Simulation Environment
    (Institute of Electrical and Electronics Engineers Inc., 2013) Efeler, Mahmut Cenk; Altınkaya, Mustafa Aziz; Gümüştekin, Şevket
    Template matching is one of the most common methods for license plate recognition. This method discards prior probabilities of license plate codes. The posterior code class probabilities constructed by including the prior probability information are expected to improve the recognition performance. The probability information that needs to be included requires extensive training data, which is quite costly to obtain. In order to generate these training images a license plate image simulator is developed with a realistic noise model. Simulated license plate images are then used to test a Bayesian decision theory based recognition procedure. Test results indicate that, with the inclusion of prior information, significant recognition gain is obtained with respect to standard template matching method at high noise levels.