Bilgisayar Mühendisliği Bölümü Tezleri

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/58

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Pattern recognition: Comparison study
(2005) Salim, Fawzı
Öne of the most important effects the field of Cognitive Science can have on the field of Computer Science is the development of technologies that make our tools more human. Evidenced by the fact that we are not currently ali using Tablet computers, accurate hand writing recognition is clearly a difficult problem to solve. Neural netvvorks field is interested with applications for many practices such as industrial process, marketing, medicine, business which is also relevant with hand writing recognition (our main study in this thesis). Hand writing recognition is an important field with applications in business 'form-filling1, including handwritten postal addresses, cheques, insurance applications, mail-order forms, tax returns, credit card sales slips, customs declarations and many others. These applications ali generale a handwritten script from an unconstrained population of writers and writing implements, which must subsequently be processed off-line by computer. To consider at the importance of neural networks and its applications, we used it in this research and we applied backpropagation algorithm to give us better results. We will present more details in the thesis especially in chapter four. The process of recognizing of handwriting from pixel information falls into a field of artificial iii l intelligence called pattern ör image recognition. Lots of work has been done in this field recently, and most techniques for pattern and image classifıcation make use of neural networks. This work implements neural networks in order to "learn" to recognize general features of hand vvritten digits using the well know backpropagation algorithm

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