Threshold center-symmetric local binary convolutional neural networks for bilingual handwritten digit recognition
Arabic and English handwritten digit recognition is a challenging problem because the writing style differs from one writer to another. In middle east countries, many official forms are prepared to be written using either Arabic or English languages. However, some people fill the form using both...
Saved in:
Main Author: | Saleh Al-Wajih, Ebrahim Qasem |
---|---|
Format: | Thesis |
Language: | English English English |
Published: |
2022
|
Subjects: | |
Online Access: | http://eprints.uthm.edu.my/8412/1/24p%20EBRAHIM%20QASEM%20SALEH%20AL-WAJIH.pdf http://eprints.uthm.edu.my/8412/2/EBRAHIM%20QASEM%20SALEH%20AL-WAJIH%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/8412/3/EBRAHIM%20QASEM%20SALEH%20AL-WAJIH%20WATERMARK.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Neural-fuzzy for handwritten digits recognition
by: Lau, Hui Keng
Published: (2003) -
Postal address handwritten recognition using convolutional neural network / Nur Hasyimah Abd Aziz
by: Abd Aziz, Nur Hasyimah
Published: (2020) -
Comparative Study Between Neural Network And Statistic In Handwritten Digit Recognition
by: Noor Azliza, Sabri
Published: (2004) -
Iris recognition using convolutional neural network /
by: Yuan, Zhuang
Published: (2018) -
Aircraft recognition using convolutional neural network /
by: Nabilah Wan Zulkipli
Published: (2018)