In base paper present about handwriting digit recognition system using Local Binary Pattern as feature extraction method and K-Nearest Neighbor as classification algorithm. So I would like to do the same work by using Artificial neural networks (ANN) as machine learning classification algorithm. In base paper the testing result on this system shows that the Local Binary Pattern Variance method can recognize handwriting digit character on MNIST dataset with accuracy level 89,81% using the best parameter value radius=4,256 and 64-bin histogram, 9 region division on the image, and 10 nearest neighbor on K-NN algorithm. When tested using the data from C1 form , the system accuration value is 70,91%. Aim of my project is to increase the accuracy of predictions using ANN.
PFA for base paper.
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Dear. I am a professional in applied mathematics. I have many experiences in Machine learning. I am sure I can help you . We can discuss details via chat. I wait for you now. Thanks.
My preferred method of freelancing is an interactive approach to project solving. I have an MSEE specializing in Digital Signal/Image Processing. I do my work in MATLAB (expert).