Recognition of CAPTCHA Characters by Supervised Machine Learning Algorithms

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F18%3APU127697" target="_blank" >RIV/00216305:26220/18:PU127697 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1016/j.ifacol.2018.07.155" target="_blank" >http://dx.doi.org/10.1016/j.ifacol.2018.07.155</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.ifacol.2018.07.155" target="_blank" >10.1016/j.ifacol.2018.07.155</a>

Result language
angličtina
Original language name
Recognition of CAPTCHA Characters by Supervised Machine Learning Algorithms
Original language description
The focus of this paper is to compare several common machine learning classication algorithms for Optical Character Recognition of CAPTCHA codes. The main part of a research focuses on the comparative study of Neural Networks, k-Nearest Neighbour, Support Vector Machines and Decision Trees implemented in MATLAB Computing environment. Achieved success rates of all analyzed algorithms overcome 89%. The main dierence in results of used algorithms is within the learning times. Based on the data found, it is possible to choose the right algorithm for the particular task.
Czech name
—
Czech description
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Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
15th IFAC Conference on Programmable Devices and Embedded Systems - PDeS 2018
ISBN
—
ISSN
2405-8963
e-ISSN
—
Number of pages
6
Pages from-to
208-213
Publisher name
Neuveden
Place of publication
Ostrava
Event location
Ostrava
Event date
May 23, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000445644900036

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