to recognize those shapes. Due to varieties in shapes there are some characters that are confusing and possibilities for misclassification are very high. Neural Networks are widely applied to pattern recognition areas. Neural Networks can be trained and then tested on various handwritten digits. This paper describes feed forward neural network with back propagation learning approach for the handwritten digit recognition. Optical Character Recognition (OCR) is a very well-studied problem in the vast
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Analysis and Neural Networks Group Department of Computing University of Exeter UK (s.singh@exeter.ac.uk) ABSTRACT Spiral structures are one of the most difficult patterns to classify. Spiral time series data has a helical movement with time that is both difficult to predict as well as classify. This paper focusses on how structural information about spirals can be useful in providing critical information to a neural network for their recognition. Results are presented on neural network solutions
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involves trying to understand human thought and an effort to build machines that imitate the human thought process. This view is the cognitive science approach to AI. Neural Network is a different paradigm for computing Von Neumann machines which are based on the processing memory abstraction of human information processing. Neural networks are like multiprocessor computer system with simple processing elements‚ high degree of interconnections‚ simple scalar messages and adaptive interaction between elements
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SOFT COMPUTING social sciences behavioral sciences the humanities economics law medicine include quantitative Human sciences methods are methods are often used separately qualitative that means numerical data precise objects conventional logic complicated mathematics computer models that means non-numerical data imprecise objects approximate reasoning interpretation manual work 2 Traditional Approaches to Computerized Modeling • Mathematical
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Comparative Evaluation Of Symbolic Learning Methods and Neural Learning Methods Shravya Reddy Konda Department of Computer Science University of Maryland‚ College Park Email: shravyak@cs.umd.edu Abstract In this paper‚ performance of symbolic learning algorithms and neural learning algorithms on different kinds of datasets has been evaluated. Experimental results on the datasets indicate that in the absence of noise‚ the performances of symbolic and neural learning methods were comparable in most of the
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УДК 681.3.01+681.327.12 http://neuroface.narod.ru ACCESS CONTROL BY FACE RECOGNITION USING NEURAL NETWORKS* Dmitry Bryliuk and Valery Starovoitov Institute of Engineering Cybernetics‚ Laboratory of Image Processing and Recognition Surganov str.‚ 6‚ 220012 Minsk‚ BELARUS E-mail: bdv78@mail.ru‚ valerys@newman.bas-net.by A Multilayer Perceptron Neural Network (NN) is considered for access control based on face image recognition. We studied robustness of NN classifiers with respect to the False
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Chapter 1 1.1 Introduction Bangladesh has a 724 lm long coastal area where south-westerly tradewind & sea breeze makes the usage of wind as a renewable energy source very visible. But‚ not much systematic wind study has been made‚ adequate information on the wind speed over the country and particularly on wind speeds at hub heights of wind machines is not available. A previous study (1986) showed that for the wind monitoring stations of Bangladesh Meteorological Department (BMD) the wind speed
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Journal of Information Technology Education Volume 10‚ 2011 Students Selection for University Course Admission at the Joint Admissions Board (Kenya) Using Trained Neural Networks Franklin Wabwoba Masinde Muliro University of Science and Technology‚ Kakamega‚ Kenya fwabwoba@gmail.com Fullgence M. Mwakondo‚ Mombasa Polytechnic University College‚ Mombasa‚ Kenya mwakondopoly@gmail.com Executive Summary Every year‚ the Joint Admission Board (JAB) is tasked to determine those students who are ex-pected
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Image Retrieval Based on Color and Texture Feature Using Artificial Neural Network Syed Sajjad Hussain#1‚ Manzoor Hashmani#2‚ Muhammad Moin uddin#3 # Faculty of Engineering‚ Sciences and Technology‚ IQRA University‚ Karachi 1 engr.sajjadrizvi@yahoo.com‚ 2mhashmani@yahoo.com‚ 3mmoin73@yahoo.com Abstract. Content-based image retrieval CBIR is a technique that helps in searching a user desired information from a huge set of image files and interpret user intentions for the desired information
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SAMPLE PROJECT PROPOSAL FINAL YEAR PROJECT PROPOSAL SUBMITTED TO THE FACULTY OF INFORMATICS’ PROJECT COMMITTEE‚ GTUC TITLE: An artificial neural network (ANN) approach to rainfall-runoff modelling PROJECT TYPE: Evaluation & development project AUTHOR(S): KWAME GYASI – 12345 KWABENA JONES – 67899 DATE: 28TH FEBRUARY‚ 2012 Background The United Nations General Assembly declared the 1990s the International Decade for Natural Disaster Reduction with the specific
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