Sürdürülebilir Kalkınma Amaçları

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• MakaleAçık Erişim2023/r/munzur/2228
  A new approach based on convolutional neural network and feature selection for recognizing vehicle types

  Doğan, Gürkan; Ergen, Burhan

  The number of vehicles used in traffic life has reached enormous dimensions today. The increase in the number of vehicles day by day causes some traffic problems along with it; such as traffic congestion, accidents, pollution, and safety. To overcome all these problems, convolutional neural networks (CNN) methods are one of the trend methods used in recent years due to their success. In this study, a new approach is proposed to use this power of CNN in low-power devices. First of all, MobileNetv1, MobileNetv2, and NASNetMobile models were optimized to increase accuracy performance. Then, an approach is proposed in which these optimized mobile CNN approaches are used only as feature extractors, and methods such as combining, selecting, and classifying the obtained features are used together. As a result of the classification made with this approach, the classification accuracy has increased by approximately 5%.

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  AtıfScopus10·OpenAlex12

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• DüzeltmeAçık Erişim2023/r/munzur/1659
  Correction to: A new approach based on convolutional neural network and feature selection for recognizing vehicle types(Iran Journal of Computer Science, 10.1007/s42044-022-00125-6)

  Doğan, Gürkan; Ergen, Burhan

  The sentence beginning 'Bu nedenle bu …' in this article should have read 'Therefore, in this study, a combination of OMobileNetv1, OMobileNetv2, ONASNetMobile CNN methods for feature extraction, LSVC method for feature selection and SVM method for classification is proposed.' The original article has been corrected.

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