Hybrid rough neural network model for signature recognition

Mohamed Elhoseny, Amir Nabil, Aboul Ella Hassanien, Diego Oliva

Результат исследований: Материалы для книги/типы отчетовГлава

13 Цитирования (Scopus)

Аннотация

This chapter introduces an offline signature recognition technique using rough neural network and rough set. Rough neural network tries to find better recognition performance to classify the input offline signature images. Rough sets have provided an array of tools which turned out to be especially adequate for conceptualization, organization, classification, and analysis of various types of data, when dealing with inexact, uncertain, or vague knowledge. Also, rough sets discover hidden pattern and regularities in application. This new hybrid technique achieves good results, since the short rough neural network algorithm is neglected by the grid features technique, and then the advantages of both techniques are integrated.

Язык оригиналаАнглийский
Название основной публикацииStudies in Computational Intelligence
ИздательSpringer Verlag
Страницы295-318
Число страниц24
DOI
СостояниеОпубликовано - 2018
Опубликовано для внешнего пользованияДа

Серия публикаций

НазваниеStudies in Computational Intelligence
Том730
ISSN (печатное издание)1860-949X

ASJC Scopus subject areas

  • Artificial Intelligence

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