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Multiple convolution neural networks approach for online handwriting recognition

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9 Apr 2013CPOL8 min read 76.8K   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.Text.RegularExpressions;

namespace SpellChecker.Dictionary.Affix
{
	/// <summary>
	///		Rule Entry for expanding base words
	/// </summary>
	public class AffixEntry
	{
		private int _ConditionCount;
		private string _AddCharacters = "";
		private int[] _Condition = new int[256] ;
		private string _StripCharacters = "";

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

		/// <summary>
		///     The characters to add to the string
		/// </summary>
		public string AddCharacters
		{
			get {return _AddCharacters;}
			set {_AddCharacters = value;}
		}

		/// <summary>
		///     The condition to be met in order to add characters
		/// </summary>
		public int[] Condition
		{
			get {return _Condition;}
			set {_Condition = value;}
		}


		/// <summary>
		///     The characters to remove before adding characters
		/// </summary>
		public string StripCharacters
		{
			get {return _StripCharacters;}
			set {_StripCharacters = value;}
		}


		/// <summary>
		///     The number of conditions that must be met
		/// </summary>
		public int ConditionCount
		{
			get {return _ConditionCount;}
			set {_ConditionCount = 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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