Paper Title :Comparison of Two Algorithms for Automated Multi-Meter Testing using Character Recognition
Author :Shreyas N. Upasani, Anil Thosar
Article Citation :Shreyas N. Upasani ,Anil Thosar ,
(2018 ) " Comparison of Two Algorithms for Automated Multi-Meter Testing using Character Recognition " ,
International Journal of Electrical, Electronics and Data Communication (IJEEDC) ,
pp. 14-18,
Volume-6,Issue-10
Abstract : Character and digit recognition is a basic building block in many automation tasks now-a-days. For keeping
records in computer and digital systems, data in digital format is required. Characters and digits recognition is done with the
help of artificial neural network. This paper proposes comparison of back-propagation algorithm and K-Nearest Neighbor
algorithm that recognizes digits and characters on digital display. This includes different techniques i.e. preprocessing,
feature extraction, training and testing of data in the system. Comparison of algorithms can be done on different criteria’s
such as accuracy, power requirement, time required for training and testing, system complexity for different set of image
dataset.
Keywords - Artificial Neural Network, Back-Propagation Preprocessing, Epochs, K-Nearest Neighbors, Training Error Rate
Type : Research paper
Published : Volume-6,Issue-10
DOIONLINE NO - IJEEDC-IRAJ-DOIONLINE-13943
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Copyright: © Institute of Research and Journals
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Published on 2018-12-27 |
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