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Research Article Peer ReviewedAt least two reviewers Open Access

İç Mekan Konumlandırma Yöntemleri

1Erzincan Binali Yıldırım University
2Erciyes University 
✉ Corresponding author: Selçuk Ökden · okdem@erciyes.edu.tr
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References

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  3. G. Félix, M. Siller, and E. N. Álvarez, “A fingerprinting indoor localization algorithm based deep learning,” Int. Conf. Ubiquitous Futur. Networks, ICUFN, vol. 2016-Augus, pp. 1006–1011, 2016.
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  8. M. Abbas, M. Elhamshary, H. Rizk, M. Torki, and M. Youssef, “WiDeep: WiFi-based accurate and robust indoor localization system using deep learning,” 2019 IEEE Int. Conf. Pervasive Comput. Commun. PerCom 2019, pp. 1–10, 2019.
  9. and T. T. H. Mehmood, N. K. Tripathi, “Indoor Positioning System Using Artificial Neural Network,” vol. 6, no. 10, pp. 1219–1225, 2010.
  10. B. Soro and C. Lee, “Performance Comparison of Indoor Fingerprinting Techniques Based on Artificial Neural Network,” IEEE Reg. 10 Annu. Int. Conf. Proceedings/TENCON, vol. 2018-Octob, no. October, pp. 56–61, 2019.
  11. M. Ibrahim, M. Torki, and M. Elnainay, “CNN based Indoor Localization using RSS Time-Series,” Proc. - IEEE Symp. Comput. Commun., pp. 1044–1049, 2018.

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Research Contributions (2019+)Peer reviewed by at least two reviewers
Open AccessCC BY 4.0
Open Discovery Metadata · DOI · OAI-PMH
Global Reachresearchers worldwide