کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4960464 1446499 2017 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Plate Recognition Using Backpropagation Neural Network and Genetic Algorithm
ترجمه فارسی عنوان
شناخت صفحات با استفاده از شبکه عصبی برگشتی و الگوریتم ژنتیک
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر علوم کامپیوتر (عمومی)
چکیده انگلیسی

Plate recognizer system is an important system. It can be used for automatic parking gate or automatic ticketing system. The purpose of this study is to determine the effectiveness of Genetic Algorithms (GA) in optimizing the number of hidden neurons, learning rate and momentum rate on Backpropagation Neural Network (BPNN) that is applied to the Automatic Plate Number Recognizer (APNR). Research done by building a GA optimized BPNN (GABPNN) and APNR system using image processing methods, including grayscale conversion, top-hat transformation, binary morphological, Otsu threshold and binary image projection. The tests conducted with backpropagation training and recognition test. The result shows that GA optimized backpropagation neural network requires 2230 epochs in the training process to be convergent, which is 36.83% faster than non-optimal backpropagation neural network, while the accuracy is 1,35% better than non-optimized backpropagation neural network.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Procedia Computer Science - Volume 116, 2017, Pages 365-372
نویسندگان
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