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BOŠTÍK, O.; KLEČKA, J.
Original Title
Recognition of CAPTCHA Characters by Supervised Machine Learning Algorithms
English Title
Type
Paper in proceedings (conference paper)
Original Abstract
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.
English abstract
Keywords
CAPTCHA, OCR, Supervised Learning, Template Matching, Decision Trees, k-NN, SVM, Neural Network
Key words in English
Authors
RIV year
2019
Released
23.04.2018
Location
Ostrava
Book
15th IFAC Conference on Programmable Devices and Embedded Systems - PDeS 2018
ISBN
2405-8963
Periodical
IFAC-PapersOnLine
Volume
2018
Number
15
State
United Kingdom of Great Britain and Northern Ireland
Pages from
208
Pages to
213
Pages count
6
BibTex
@inproceedings{BUT147094, author="Ondřej {Boštík} and Jan {Klečka}", title="Recognition of CAPTCHA Characters by Supervised Machine Learning Algorithms", booktitle="15th IFAC Conference on Programmable Devices and Embedded Systems - PDeS 2018", year="2018", journal="IFAC-PapersOnLine", volume="2018", number="15", pages="208--213", address="Ostrava", doi="10.1016/j.ifacol.2018.07.155", issn="2405-8971" }
Documents
PDES18_BostikPDES2018