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Multiple convolution neural networks approach for online handwriting recognition

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9 Apr 2013CPOL8 min read 76.5K   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;

namespace SpellChecker
{
	/// <summary>
	///     Class sent to the event handler when the DoubleWord or 
	///     MisspelledWord event occurs
	/// </summary>
	public class SpellingEventArgs : EventArgs 
	{
		private int _TextIndex;
		private string _Word;
		private int _WordIndex;

		/// <summary>
		///     Constructor used to pass in properties
		/// </summary>
		public SpellingEventArgs(string word, int wordIndex, int textIndex)
		{
			_Word = word;
			_WordIndex = wordIndex;
			_TextIndex = textIndex;
		}

		/// <summary>
		///     Text index of the WordEvent
		/// </summary>
		public int TextIndex
		{
			get {return _TextIndex;}
		}

		/// <summary>
		///     Word that caused the WordEvent
		/// </summary>
		public string Word
		{
			get {return _Word;}
		}

		/// <summary>
		///     Word index of the WordEvent
		/// </summary>
		public int WordIndex
		{
			get {return _WordIndex;}
		}

	} // Class SpellingEventArgs
}

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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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