Arabic Handwritten Alphanumeric Character Recognition Using Very Deep Neural Network
The traditional algorithms for recognizing handwritten alphanumeric characters are dependent on hand-designed features. In recent days, deep learning techniques have brought about new breakthrough technology for pattern recognition applications, especially for handwritten recognition. However, deepe...
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| Format: | Article |
| Language: | English |
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MDPI AG
2017-08-01
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| Series: | Information |
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| Online Access: | https://www.mdpi.com/2078-2489/8/3/105 |
| _version_ | 1819236131848323072 |
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| author | MohammedAli Mudhsh Rolla Almodfer |
| author_facet | MohammedAli Mudhsh Rolla Almodfer |
| author_sort | MohammedAli Mudhsh |
| collection | DOAJ |
| description | The traditional algorithms for recognizing handwritten alphanumeric characters are dependent on hand-designed features. In recent days, deep learning techniques have brought about new breakthrough technology for pattern recognition applications, especially for handwritten recognition. However, deeper networks are needed to deliver state-of-the-art results in this area. In this paper, inspired by the success of the very deep state-of-the-art VGGNet, we propose Alphanumeric VGG net for Arabic handwritten alphanumeric character recognition. Alphanumeric VGG net is constructed by thirteen convolutional layers, two max-pooling layers, and three fully-connected layers. The proposed model is fast and reliable, which improves the classification performance. Besides, this model has also reduced the overall complexity of VGGNet. We evaluated our approach on two benchmarking databases. We have achieved very promising results, with a validation accuracy of 99.66% for the ADBase database and 97.32% for the HACDB database. |
| first_indexed | 2024-12-23T12:59:34Z |
| format | Article |
| id | doaj.art-e10324c3dc9d432da7c359ae87ceca62 |
| institution | Directory Open Access Journal |
| issn | 2078-2489 |
| language | English |
| last_indexed | 2024-12-23T12:59:34Z |
| publishDate | 2017-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Information |
| spelling | doaj.art-e10324c3dc9d432da7c359ae87ceca622022-12-21T17:46:03ZengMDPI AGInformation2078-24892017-08-018310510.3390/info8030105info8030105Arabic Handwritten Alphanumeric Character Recognition Using Very Deep Neural NetworkMohammedAli Mudhsh0Rolla Almodfer1School of Computer Science, Wuhan University of Technology, Luo Shi Road, Wuhan 430070, ChinaSchool of Computer Science, Wuhan University of Technology, Luo Shi Road, Wuhan 430070, ChinaThe traditional algorithms for recognizing handwritten alphanumeric characters are dependent on hand-designed features. In recent days, deep learning techniques have brought about new breakthrough technology for pattern recognition applications, especially for handwritten recognition. However, deeper networks are needed to deliver state-of-the-art results in this area. In this paper, inspired by the success of the very deep state-of-the-art VGGNet, we propose Alphanumeric VGG net for Arabic handwritten alphanumeric character recognition. Alphanumeric VGG net is constructed by thirteen convolutional layers, two max-pooling layers, and three fully-connected layers. The proposed model is fast and reliable, which improves the classification performance. Besides, this model has also reduced the overall complexity of VGGNet. We evaluated our approach on two benchmarking databases. We have achieved very promising results, with a validation accuracy of 99.66% for the ADBase database and 97.32% for the HACDB database.https://www.mdpi.com/2078-2489/8/3/105alphanumeric recognitionArabic handwrittendeep learningVGGNetdropoutaugmentation |
| spellingShingle | MohammedAli Mudhsh Rolla Almodfer Arabic Handwritten Alphanumeric Character Recognition Using Very Deep Neural Network Information alphanumeric recognition Arabic handwritten deep learning VGGNet dropout augmentation |
| title | Arabic Handwritten Alphanumeric Character Recognition Using Very Deep Neural Network |
| title_full | Arabic Handwritten Alphanumeric Character Recognition Using Very Deep Neural Network |
| title_fullStr | Arabic Handwritten Alphanumeric Character Recognition Using Very Deep Neural Network |
| title_full_unstemmed | Arabic Handwritten Alphanumeric Character Recognition Using Very Deep Neural Network |
| title_short | Arabic Handwritten Alphanumeric Character Recognition Using Very Deep Neural Network |
| title_sort | arabic handwritten alphanumeric character recognition using very deep neural network |
| topic | alphanumeric recognition Arabic handwritten deep learning VGGNet dropout augmentation |
| url | https://www.mdpi.com/2078-2489/8/3/105 |
| work_keys_str_mv | AT mohammedalimudhsh arabichandwrittenalphanumericcharacterrecognitionusingverydeepneuralnetwork AT rollaalmodfer arabichandwrittenalphanumericcharacterrecognitionusingverydeepneuralnetwork |