2026-10-29T20:44:45Zhttps://munzur-rdlopen.rawdatalibrary.net/oai/request

oai:munzur-rdlopen.rawdatalibrary.net:munzur/36942026-10-28T15:30:58Zopenairecom_munzur_1col_munzur_2com_munzur_8col_munzur_154

Classification of Hand-Drawn Circuit Components by Considering the Analysis of Current MethodsGunay, MihribanKoseoglu, Muratcircuit componentclassificationCNNKNNSVMIn this paper, at first, existing classification methods for classifying hand drawn circuits and circuit components are briefly introduced by examining advantages and disadvantages of each classification method. The handled methods are Support Vector Machine method (SVM), nearest neighbor method (KNN) and convolutional neural network method (CNN). Then, in the experimental part of the study, four different hand-drawn circuit components, which are diode, capacitor, resistor and ac voltage source, have been tried to be classified by using CNN method which is a highly recommended classification method in literature. The classification tables and graphics have been presented for the performed study. According to the obtained results and accuracy rate, it is concluded that CNN method can be used reliably to achieve high performance in the classification of hand-drawn circuit components.Institute of Electrical and Electronics Engineers Inc.2020Conference Objecthttps://rdlopen.rawdatalibrary.net/r/munzur/3694https://doi.org/10.1109/ismsit50672.2020.9255047978-172819090-7en4th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2020 - Proceedingsinfo:eu-repo/semantics/closedAccessinfo:eu-repo/semantics/conferenceObjecthttps://munzur-rdlopen.rawdatalibrary.net/tr/items/munzur/3694