About me

Zafer CÖMERT is currently Asst. Prof. in the Department of Software Engineering at Samsun University. He received his BSc degree in Electronics and Computer Education from Firat University in 2008. He also received his MSc degree in Computer and Instructional Technologies from Firat University in 2012. He has finished Ph.D. work on the classification of cardiotocography data with machine learning techniques in the Department of Computer Engineering at Inönü University in 2017.

Expertise: Biomedical Signal Processing, Machine Learning, Clinical Decision Support Systems

A. International Publications indexed by SCI, SSCI, SCI-E

  1. Toğaçar M, Ergen B, Cömert Z. A Deep Feature Learning Model for Pneumonia Detection Applying a Combination of mRMR Feature Selection and Machine Learning Models. IRBM 2019. doi:https://doi.org/10.1016/j.irbm.2019.10.006.
  2. E. Başaran, Z. Cömert, Y. Çelik, Convolutional neural network approach for automatic tympanic membrane detection and classification, Biomed. Signal Process. Control. 56 (2020) 101734. doi:https://doi.org/10.1016/j.bspc.2019.101734.
  3. Daldal N, Cömert Z, Polat K. Automatic determination of digital modulation types with different noises using Convolutional Neural Network based on time-frequency information. Appl Soft Comput 2019:105834. doi:https://doi.org/10.1016/j.asoc.2019.105834.
  4. Ü. Budak, Z. Cömert, M. Çıbuk, A. Şengür, DCCMED-Net: Densely connected and concatenated multi Encoder-Decoder CNNs for retinal vessel extraction from fundus images, Med. Hypotheses. 134 (2020) 109426. doi:https://doi.org/10.1016/j.mehy.2019.109426.
  5. Budak Ü, Cömert Z, Rashid ZN, Şengür A, Çıbuk M. Computer-aided diagnosis system combining FCN and Bi-LSTM model for efficient breast cancer detection from histopathological images. Appl Soft Comput 2019:105765. doi:https://doi.org/10.1016/j.asoc.2019.105765.
  6. Cömert Z, Şengür A, Akbulut Y, Budak Ü, Kocamaz AF, Bajaj V. Efficient approach for digitization of the cardiotocography signals. Phys A Stat Mech Its Appl 2019:122725. doi:https://doi.org/10.1016/j.physa.2019.122725.
  7. Y. Altuntaş, Z. Cömert, and A. F. Kocamaz, “Identification of haploid and diploid maize seeds using convolutional neural networks and a transfer learning approach,” Comput. Electron. Agric., vol. 163, p. 104874, 2019.
  8. Z. Cömert, A. Şengür, Y. Akbulut, Ü. Budak, A. F. Kocamaz, and S. Güngör, “A Simple and Effective Approach for Digitization of the CTG Signals from CTG Traces,” IRBM, 2019.
  9. Z. Zhao, Y. Zhang, Z. Comert, Y. Deng, Computer-Aided Diagnosis System of Fetal Hypoxia Incorporating Recurrence Plot With Convolutional Neural Network, Front. Physiol. 10 (2019) 255. doi:10.3389/fphys.2019.00255.
  10. Cömert, Z., Kocamaz, A. F., & Subha, V. (2018). Prognostic model based on image-based time-frequency features and genetic algorithm for fetal hypoxia assessment. Computers in biology and medicine.
  11. Cömert, Z., & Kocamaz, A. F. (2018). Open-access software for analysis of fetal heart rate signals. Biomedical Signal Processing and Control, 45, 98-108.
  12. Cömert, Z., and Kocamaz, A. F.,  (2017), “Comparison of Machine Learning Techniques for Fetal Heart Rate Classification” Acta Physica Polonica A, Vol. 132 (2017), No. 3. 
  13. Varank, İ., Erkoç, F. M., Adıgüzel, T., Cömert, Z., & Zengin, E. (2014). “Effectiveness of an Online Automated Evaluation and Feedback System in an Introductory Computer Literacy Course”. Eurasia Journal of Mathematics, Science & Technology Education, 395-404.

B. International Publication

  1. Cömert Z, Sengür A, Budak Ü, Kocamaz AF. Prediction of intrapartum fetal hypoxia considering feature selection algorithms and machine learning models. Heal Inf Sci Syst 2019;7:17. doi:10.1007/s13755-019-0079-z.
  2. Cömert, Zafer and Özge CÖMERT. "A Study of Technologies Used in Learning Management Systems and Evaluation of New Trend Algorithms." Bitlis Eren Üniversitesi Sosyal Bilimler Enstitüsü Dergisi 7.1 (2017): 286-297.
  3. Z. Cömert, A.F. Kocamaz, “A Study of Artificial Neural Network Training Algorithms for Classification of Cardiotocography Signals”, Bitlis Eren Univ. J. Sci. Technol. 7 (2017) 93–103.
  4. A. Diker, Z. Cömert, E. Avcı, “A Diagnostic Model for Identification of Myocardial Infarction from Electrocardiography Signals”, Bitlis Eren Univ. J. Sci. Technol. 7 (2017) 132–139
  5. Z. Comert and A. F. Kocamaz, (2016), “Evaluation of Fetal Distress Diagnosis during Delivery Stages based on Linear and Nonlinear Features of Fetal Heart Rate for Neural Network Community,” Int. J. Comput. Appl., vol. 156, no. 4, pp. 26–31.
  6. Sevindik, T., & Cömert, Z. (2011). “Öğrenme Nesnelerinin Sınıflandırılması için Semantik Web Tabanlı İnsan Bilgisayar Etkileşimi”. NWSA, 816 - 822.
  7. Sevindik, T., & Cömert, Z. (2010). “Using Algorithms for Evaluation in Web-Based Distance Education”. Elsevier.
  8. Sevindik T., Cömert, Z. (2010). “Virtual Education Environments and Web Mining”. Elsevier, 5120-5124

C. International Publications of International Congresses and Symposium 

  1. Şengür A, Akbulut Y, Budak Ü, Cömert Z. White Blood Cell Classification Based on Shape and Deep Features. 2019 Int. Artif. Intell. Data Process. Symp., 2019, p. 1–4. doi:10.1109/IDAP.2019.8875945.
  2. Basaran E, Sengur A, Comert Z, Budak U, Celik Y, Velappan S. Normal and Acute Tympanic Membrane Diagnosis based on Gray Level Co-Occurrence Matrix and Artificial Neural Networks. 2019 Int. Artif. Intell. Data Process. Symp., 2019, p. 1–6. doi:10.1109/IDAP.2019.8875973.
  3. Z. Cömert, A.F. Kocamaz, Fetal Hypoxia Detection Based on Deep Convolutional Neural Network with Transfer Learning Approach, in: R. Silhavy (Ed.), Softw. Eng. Algorithms Intell. Syst., Springer International Publishing, Cham, 2019: pp. 239–248. 
  4. Diker, A., et. al., “Classification of ECG Signal by using Machine Learning Methods”, 26th Signal Processing and Communications Applications Conference (SIU), İzmir, Turkey, 2018.
  5. Aydın, M. C., et. al., “Estimation Of Flow Series Using Discrete Wavelet Analysis And Artificial Neural Networks”, 4th International Conference on Engineering and Natural Sciences, Kiev, Ukraine, 2018.  
  6. Cömert, Z. et. al., “Performance Evaluation of Empirical Mode Decomposition and Discrete Wavelet Transform for Computerized Hypoxia Detection and Prediction”, 26th Signal Processing and Communications Applications Conference (SIU), İzmir, Turkey, 2018.
  7. Cömert, Z. et. al., “The Influences of Different Window Functions and Lengths on Image-based Time-Frequency Features of Fetal Heart Rate Signals”, 26th Signal Processing and Communications Applications Conference (SIU), İzmir, Turkey, 2018.
  8. Diker, A., et. al., “Intelligent System based on Genetic Algorithm and Support Vector Machine for Detection of Myocardial Infarction from ECG signals”,  26th Signal Processing and Communications Applications Conference (SIU), İzmir, Turkey, 2018.
  9. Cömert, Ö., Cömert, Z., and Genç, Z., "Distance Education Technologies and New Trends in Distance Education", International Conference on Multidisciplinary, Engineering, Science, Education and Technology (IMESET'17)", Bitlis, Turkey, 2017.
  10. Cömert, Z., and Kocamaz, A. F., (2017), "Using Wavelet Transform for Cardiotocography Signals Classification", 25th Signal Processing and Communications Applications Conference, Antalya, Turkey.
  11. Cömert, Z., and Kocamaz, A. F., (2017), "Cardiotocography Analysis based on Segmentation-based Fractal Texture Decomposition and Extreme Learning Machine", 25th Signal Processing and Communications Applications Conference, Antalya, Turkey.
  12. Cömert, Z., and Kocamaz, A. F., (2017), "A Novel Software for Comprehensive Analysis of Cardiotocography Signals, CTG-OAS", International Artificial Intelligence and Data Processing Symposium (IDAP'17), Malatya, Turkey.
  13. Z. Cömert and A. F. Kocamaz, (2017), "CTG-OAS: Open Access Software for Analysis of Fetal Heart Rate Signals," in 4th International Conference on Computational and Experimental Science and Engineering, Antalya, Turkey.
  14. Z. Cömert and A. F. Kocamaz, (2017), "Evaluation of Feature Selection Algorithms on Cardiotocography Data," in 4th International Conference on Computational and Experimental Science and Engineering, Antalya, Turkey.
  15. Z. Cömert and A. F. Kocamaz, (2016), "Comparison of Machine Learning Techniques for Fetal Heart Rate Classification," in International Conference on Computational and Experimental Science and Engineering, Antalya, Turkey.
  16. Z. Cömert and A. F. Kocamaz, (2016), "Performance Comparison of Neural Network Training Algorithms for Fetal Heart Rate Patterns," in International Conference on Computational and Experimental Science and Engineering, Antalya, Turkey.
  17. Z. Cömert and A. F. Kocamaz, (2016), "A Study Based on Gray Level Co-Occurrence Matrix and Neural Network Community for Determination of Hypoxic Fetuses," in International Artificial Intelligence and Data Processing Symposium'16, Malatya, Turkey.
  18. Z. Cömert, A. F. Kocamaz and S. Güngör, (2016), "Classification and Comparison of Cardiotocography Signals with Artificial Neural Network and Extreme Learning Machine", 24th Signal Processing and Communications Applications Conference, Zonguldak.
  19. Çıbuk, M., & Cömert, Z. (2015). “Elektronik Talep Yönetim Sistemi”. International Science and Technology Conference. Petersburg, 753-759 pp, Russia: ISTE-C
  20. Cömert, Z., & Sevindik, T. (2011). “The use of Google Chart for Visual Presentation of Data in Semantic Web Based Learning Management System”. 5th International Computer & Instructional Technologies Symposium (s. 902-908). Elazığ - Turkey: Fırat University.
  21. Sevindik, T., Genç, Z., Kayışlı, K., & Cömert, Z. (2011). “Education Platform in E-Government Applications”. 5th International Computer & Instructional Technologies Symposium (s. 317-323). Elazığ-Turkey: Fırat University.

D. Publications of National Congresses and Symposium 

  1. Cömert, Z., Kocamaz, A. F., & Çıbuk, M. (2015). “Web Tabanlı Hibrit Bir Uygulama Modeliyle Personel Bilgi Sistemi Tasarımı”. Akademik Bilişim. Eskişehir.
  2. Z. Cömert ve A. F. Kocamaz, (2015), "Determination of QT Interval on Synthetic Electrocardiogram", Sinyal İşleme ve İletişim Kurultayı, Malatya.

E. Projects 

  1. TUBİTAK 1512, Teknogirişim Sermayesi Desteği Programı (BiGG), Kardiyotokografi Cihazına Dayalı Bilgisayarlı Fetal Kalp Hızı Analiz Sisteminin Geliştirilmesi, Yürütücü
  2. Kamu Kurumları ile Ortak Geliştirilen Proje, (2014-2016),Egzoz Gazı Emisyon Ölçümü Takip Sistemi Projesi”, Bitlis Eren Üniversitesi, Çevre ve Şehircilik Bakanlığı, Araştırmacı
  3. Kamu Kurumları ile Ortak Geliştirilen Proje, (2014-2016), Afet Riski Haritası Hazırlanması, Coğrafi Bilgi Sistem Tabanlı Otomasyon Sistemlerinin Araştırılması ve Geliştirilmesi İşi”, Bitlis Eren Üniversitesi, Çevre ve Şehircilik Bakanlığı, Araştırmacı
  4. TUBITAK 1001 Projesi, (2012-2014), “Temel Bilgi Teknolojisi Becerilerinin Kazandırılmasına Yönelik Geliştirilen Otomatik Değerlendirme ve Geri Bildirim Sistemi İle Verilecek Sosyal Paylaşım Temelli ve Bilgisayar Temelli Geri Bildirimin Öğrenme Performansına ve Öz-Yeterlilik Algısına Etkisi”, Burslu doktora öğrencisi.
  5. Bitlis Eren Üniversitesi ve Saban Üniversitesi İşbirliği ile Geliştirilen Meslek Edindirme Projesi, (2012-2013) “Bilişim Teknolojileri Meslek Edindirme Programı (BİTMEP)”, Eğitmen

E. Chapters

  1. Z. Cömert, A.F. Kocamaz, Fetal Hypoxia Detection Based on Deep Convolutional Neural Network with Transfer Learning Approach, in: R. Silhavy (Ed.), Softw. Eng. Algorithms Intell. Syst., Springer International Publishing, Cham, 2019: pp. 239–248. 

 

 

2019-11-08, Cuma