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Multiple convolution neural networks approach for online handwriting recognition

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9 Apr 2013CPOL8 min read 75.9K   25.1K   74  
The research focuses on the presentation of word recognition technique for an online handwriting recognition system which uses multiple component neural networks (MCNN) as the exchangeable parts of the classifier.
using System;
using System.Collections;
using System.Text.RegularExpressions;

namespace SpellChecker.Dictionary.Affix
{
	/// <summary>
	///		Rule for expanding base words
	/// </summary>
	public class AffixRule
	{
		private bool _AllowCombine = false;
		private AffixEntryCollection _AffixEntries = new AffixEntryCollection();
		private string _Name = "";

		/// <summary>
		///     Initializes a new instance of the class
		/// </summary>
		public AffixRule()
		{
		}

		/// <summary>
		///     Allow combining prefix and suffix
		/// </summary>
		public bool AllowCombine
		{
			get {return _AllowCombine;}
			set {_AllowCombine = value;}
		}

		/// <summary>
		///     Collection of text entries that make up this rule
		/// </summary>
		public AffixEntryCollection AffixEntries
		{
			get {return _AffixEntries;}
			set {_AffixEntries = value;}
		}

		/// <summary>
		///     Name of the Affix rule
		/// </summary>
		public string Name
		{
			get {return _Name;}
			set {_Name = value;}
		}

	}
}

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This article, along with any associated source code and files, is licensed under The Code Project Open License (CPOL)


Written By
Vietnam Maritime University
Vietnam Vietnam
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