Gökhan ALTAN
He received a Bachelor’s degree in Computer Systems Education from Selcuk University (2008), also has a Master’s degree in the Department of Computer and Electronics Science from Selcuk University (2011). Ph.D.: Mustafa Kemal University, Department of Informatics, Computer Engineering (2014-2018).
His scientific areas: Artificial Intelligence, Digital Signal Processing, Machine Learning, and Deep Learning in particular.
JOURNAL PAPERS (SCI, SCI-Expanded, AHCI, EI, and other indexes)
| PRINTED | |
| A.25. G. ALTAN, S. ALKAN, D. BALEANU, A novel fractional operator application for neural networks using proportional Caputo derivative, Neural Computing and Applications, Vol. 35, pp.3101–3114, 2023, (SCI-E) DOI:https://dx.doi.org/10.1007/s00521-022-07728-x |  |
| A.24. G. ALTAN, F. PAŞALIOĞLU, Android malware application detection using multi-layer perceptron, Journal of Intelligent Systems with Applications, Vol. 5, Issue.2, pp. 95 – 99, 2022, DOI:https://doi.org/10.54856/jiswa.202212221 | |
| A.23. G. ALTAN, S.S. NARLI, CLAHE based Enhancement to Transfer Learning in COVID-19 Detection, Gazi Journal of Engineering Sciences,Vol.8,No.2,pp.406-416, 2022. DOI:https://dx.doi.org/10.30855/gmbd.0705001 | |
| A.22. G. ALTAN, Breast Cancer Diagnosis using Deep Belief Networks on ROI Images, Pamukkale University Journal of Engineering Sciences (PAJES), Vol. 28 Issue:2, pp. 286-291, 2022, DOI:https://dx.doi.org/10.5505/pajes.2021.38668 | |
| A.21. G. ALTAN, DeepOCT: An explainable deep learning architecture to analyze macular edema on OCT images, Engineering Science and Technology, an International Journal, Vol. 34, p.101091, 2022 (SCI-E), DOI:https://doi.org/10.1016/j.jestch.2021.101091 | |
| A.20. G. ALTAN, G. İNAT, EEG based spatial attention shifts detection using time-frequency features on empirical wavelet transform. Journal of Intelligent Systems with Applications, Vol. 4, Issue. 2, p. 144-149, 2021, DOI:https://doi.org/10.54856/jiswa.202112181 | |
| A.19. İ. ABASIKELES-TURGUT, G. ALTAN, A fully distributed energy-aware multi-level clustering and routing for WSN-based IoT, Transactions on Emerging Telecommunications Technologies, Vol. 32, Issue. 12, e4355, 2021 (SCI-E), DOI:https://doi.org/10.1002/ett.4355 | |
| A.18. G. ALTAN, A. YAYIK & Y. KUTLU, Deep Learning with ConvNET Predicts Imagery Tasks Through EEG, Neural Processing Letters, Springer, Vol. 53, pp. 2917–2932, 2021 (SCI-E), DOI:https://doi.org/10.1007/s11063-021-10533-7 | |
| A.17. S.S NARLI, G. ALTAN, Impact Of Local Histogram Equalization On Deep Learning Architectures For Diagnosis Of COVID-19 On Chest X-Rays, Machester Journal of Artificial Intelligence and Applied Sciences (MJAIAS), Vol.2, Issue.1, pp. 11 – 17, 2021 | |
| A.16. G. ALTAN, SecureDeepNet-IoT: A Deep Learning application for Invasion Detection in IIoT sensing systems, Transactions on Emerging Telecommunications Technologies, Wiley, Vol.32, Issue.4, e4228, 2021 (SCI-E) DOI: https://doi.org/10.1002/ett.4228 | |
| A.15. G. ALTAN, Deep Learning-based Mammogram Classification for Breast Cancer, International Journal of Intelligent Systems and Applications in Engineering, Vol. 8, Issue. 4, pp. 171– 176, 2020. DOI: https://doi.org/10.18201/ijisae.2020466308 | |
| A.14. G. ALTAN, Performance Evaluation of Capsule Networks for Classification of Plant Leaf Diseases, International Journal of Applied Mathematics Electronics and Computers , Vol. 8 Issue.3 , pp.57 – 63, 2020. DOI: http://doi.org/10.18100/ijamec.797392 | |
| A.13. G. ALTAN, Y. KUTLU & A.GöKCEN, Chronic Obstructive Pulmonary Disease Severity Analysis using Deep Learning on Multi-channel Lung Sounds, Turk J Elec Eng & Comp Sci, Vol. 28: pp: 2979 – 2996, 2020, (SCI-E) http://doi.org/10.3906/elk-2004-68 | |
| A.12. G. ALTAN, Y. KUTLU, N. ALLAHVERDİ, Deep Learning on Computerized Analysis of Chronic Obstructive Pulmonary Disease, IEEE Journal of Biomedical and Health Informatics, Vol.24, Issue. 5, 2020, Pages 1344 – 1350, ISSN 2168-2194, (SCI-E) https://doi.org/10.1109/JBHI.2019.2931395 | |
| A.11. G. ALTAN, Y. KUTLU, M. YENİAD, ECG Based Human Identification Using Second Order Difference Plots, Computer Methods and Programs in Biomedicine, Vol.170,March 2019, Pages 81-93, ISSN 0169-2607, (SCI-E) https://doi.org/10.1016/j.cmpb.2019.01.010 | |
| A.10. G. ALTAN, Y. KUTLU, Superiorities of Deep Extreme Learning Machines against Convolutional Neural Networks, Natural and Engineering Sciences, Supplement,30 December 2018, ISSN: 2458-8989, Vol.3, Issue.3, pp.103-109 | |
| A.9. G. ALTAN, Y. KUTLU, Generative Autoencoder Kernels on Deep Learning for Brain Activity Analysis, Natural and Engineering Sciences, 10 October 2018, ISSN: 2458-8989, Vol.3, Issue.3, pp.311–322, https://doi.org/10.28978/nesciences.468978 | |
| A.8. G. ALTAN, Y. KUTLU, Hessenberg Elm Autoencoder Kernel For Deep Learning, Journal of Engineering Technology and Applied Sciences, Volume 3, Issue 2, 30 August 2018, pp. 141-151, e-ISSN 2548-0391, https://doi.org/10.30931/jetas.450252. | |
| A.7. G. ALTAN, Y. KUTLU, A. Ö. PEKMEZCİ & S. NURAL, Deep Learning with 3D-Second Order Difference Plot on Respiratory Sounds, Biomedical Signal Processing and Control, ELSEVIER, Volume 45, August 2018, Pages 58-69, ISSN 1746-8094, (SCI-E) https://doi.org/10.1016/j.bspc.2018.05.014. | |
| A.6. G. ALTAN, Y. KUTLU, Y. GARBİ, A. Ö. PEKMEZCİ & S. NURAL, Multimedia Respiratory Database (RespiratoryDatabase@TR): Auscultation Sounds And Chest X-rays, Natural and Engineering Sciences, 2017, 2458-8989, 2, 3, pp.59–72, DOI: https://doi.org/10.28978/nesciences.349282 | |
| A.5. Y. KUTLU, G. ALTAN, B. İŞÇİMEN, SA. DOĞDU, C. TURAN, Recognition of Species of Triglidae Family using Deep Learning, Journal of Black Sea / Mediterranean Environment 23 (1), April 2017, Pages 56-65, ISSN:1304-9550 | |
| A.4. G. ALTAN, N. ALLAHVERDi, Y. KUTLU, Diagnosis of Coronary Artery Disease Using Deep Belief Networks, European Journal of Engineering and Natural Sciences Vol:2 Issue(1),ISSN:2458-8156, March 2017, Pages 29-36 | |
| A.3. G. ALTAN, Y. KUTLU, N. ALLAHVERDi, Deep Belief Networks Based Brain Activity Classification Using EEG from Slow Cortical Potentials in Stroke, International Journal of Applied Mathematics, Electronics and Computers, Volume 4, Special Issue I,December 2016, Pages 205-210, ISSN 2147-8228, http://dx.doi.org/10.18100/ijamec.270307 | |
| A.2. G. ALTAN, Y. KUTLU, N. ALLAHVERDi, A Multistage Deep Belief Networks Application on Arrhythmia Classification, International Journal of Intelligent Systems and Applications in Engineering, Vol. 4, Special Issue 1, December 2016, Pages 23-34, ISSN 2147-6799, https://doi.org/10.18201/ijisae.2016SpecialIssue-146978 | |
| A.1. G. ALTAN, Y. KUTLU, N. ALLAHVERDi, A new approach to early diagnosis of congestive heart failure disease by using Hilbert – Huang transform, Computer Methods and Programs in Biomedicine, Volume 137, December 2016, Pages 23-34, ISSN 0169-2607, (SCI-E) http://dx.doi.org/10.1016/j.cmpb.2016.09.003 | |
NATIONAL JOURNALS
| D.3. G. ALTAN, DeepGraphNet: Grafiklerin Sınıflandırılmasında Derin Öğrenme Modelleri (DeepGraphNet: Deep Learning Models in the Classification of Graphs), European Journal of Science and Technology (EJOSAT), Special Issue, pp. 319-329, October 2019, DOI: https://doi.org/10.31590/ejosat.638256 (TRDizin) | |
| D.2. G. ALTAN, Y. KUTLU, A.Ö. PEKMEZCİ, S. NURAL, Hilbert-Huang Dönüşümü ve Derin Öğrenme Kullanarak Akciğer Seslerinde Astım Teşhisi (The Diagnosis of Asthma using Hilbert-Huang Transform and Deep Learning on Lung Sounds, J. Intel. Syst. App., Vol.2 Sayı.2, (2019), p.267-272, DOI: https://doi.org/10.54856/jiswa.201912073 | |
| D.1. G. ALTAN, A. YAYIK, Y. KUTLU, S. YILDIRIM, E. YILDIRIM, Konjestif Kalp Yetmezliğinin Hilbert-Huang Dönüşüm ile Analizi (Analyse of Congestive Heart Failure Using Hilbert- Huang Transform), DEU J. Sci. Eng. Vol. 16 (2014), p.94-103. ISSN: 1302-9304 | |
INTERNATIONAL PROCEEDINGS
| B.17. G. ALTAN, Fine-tuning Deep Learning Models to Identify Pepper Leaf Diseases, International Conference on Artificial Intelligence towards Industry 4.0 (ICAII4’21), 2021, pp.41-48, Hatay, Turkey | |
| B.16. G. ALTAN, Underwater fish recognition using deep learning, International Conference on Engineering Technologies (ICENTE’21), 2021, pp.53-55, Konya, Turkey | |
| B.15. S.S. NARLI,G. ALTAN, Denoising Medical X-ray Images Using Block-matching and 3D Filtering. International Conference on Artificial Intelligence towards Industry 4.0 (ICAII4.0), 2019, pp. 245-251, Hatay, Turkey | |
| B.14. T. AÇIL, Y. KUTLU, G. ALTAN, İris Görüntülerinden Derin Öğrenme ile Cinsiyet Sınıflandırma, World Symposium of Multidisciplinary Research (WOSMUR2018), 2018, Vol.2 No.2, pp.25-31, Mersin, Turkey | |
| B.13. G. ALTAN, Y. KUTLU, C. TURAN, Performance of Deep Extreme Learning Machines with LU Kernel on Morphometric Fish Recognition, 3rd International Congress on Applied Ichthyology & Aquatic Environment (HydroMedit2018), 2018, pp.490-494, Volos, Greece | |
| B.12. G. ALTAN, Y. KUTLU, The Impact of Heart Sounds as Additional Features on COPD Analysis using Deep Learning, 1st Zeugma International Congress on Multidisciplinary Congress, 13-16 September 2018, Gaziantep, Turkey, pp. 840-844 | |
| B.11. N. ALLAHVERDİ, G. ALTAN & Y. KUTLU, Deep Learning for COPD Analysis Using Lung Sounds, 6th International Conference on Control and Optimization with Industrial Applications (COIA2018), July 11-13, 2018, Baku, Azerbaijan, pp.74-76 | |
| B.10. G. ALTAN, Y. KUTLU & A.YAYIK, Hessenberg ELM Autoencoder Kernel For Deep Learning, 5th International Congress on Fundamental and Applied Sciences (ICFAS2018), June 18-22, 2018, Skopje, Macedonia, ICFAS2018-ID:1153 (Abstract) | |
| B.9. G. ALTAN, N. ALLAHVERDİ & Y. KUTLU, A Multistage Deep Learning Algorithm for Detecting Arrhythmia, 1st International Conference on Computer Applications & Information Security (ICCAIS), Riyadh, Saudi Arabia, April 4-5, 2018, DOI: 10.1109/CAIS.2018.8441942 | |
| B.8. G. ALTAN, Y. KUTLU, A. Ö. PEKMEZCİ & A. YAYIK, Diagnosis of Chronic Obstructive Pulmonary Disease using Deep Extreme Learning Machines with LU Autoencoder Kernel, 7th International Conference on Advanced Technologies (ICAT’18), 28 April-1 May 2018, p. 618-622 (BEST PAPER AWARD) | |
| B.7. G. ALTAN, Y. KUTLU, A. Ö. PEKMEZCİ & S. NURAL, Asthma Analysis using Deep Learning, Full Text, 7th International Conference on Advanced Technologies (ICAT’18), 28 April-1 May 2018, p. 613-617 | |
| B.6. G. ALTAN, Y. KUTLU, A. Ö. PEKMEZCİ, S. NURAL, Y. GARBİ & E. ARSLAN, Diagnosis of Chronic Obstructive Pulmonary Disease using Wavelet Transform Analysis from Auscultation Sounds, 4th International Conference on Pure and Applied Sciences (Renewable Energy) (ICPAS), 23-25 Nov. 2017, p.58 (Abstract) | |
| B.5. G. ALTAN, Y. KUTLU, Y. GARBİ, A. Ö. PEKMEZCİ & S. NURAL, Efficiency Of Three-dimensional Second Order Difference Plot And Deep Learning On Respiratory Sounds, (Abstract), International Conference on Mathematics and Engineering, 10-12 May 2017, p. 328 (Abstract) | |
| B.4. G. ALTAN, Y. KUTLU, N. ALLAHVERDi, Deep Belief Network Based Brain Activity Classification Using EEG From Slow Cortical Potentials in Stroke, 3rd International Conference on Advanced Technology & Sciences (ICAT’16), 2016, pp:233-239 | |
| B.3. Y. KUTLU, G. ALTAN, N. ALLAHVERDi, Arrhythmia Classification Using Waveform ECG Signals, 3rd International Conference on Advanced Technology & Sciences (ICAT’16), 2016, pp:240-245 | |
| B.2. N. ALLAHVERDi, G. ALTAN, Y. KUTLU, Diagnosis of Coronary Artery Disease Using Deep Belief Networks, 2nd International Conference on Engineering and Natural Sciences (ICENS2016),24-28 May 2016, Sarajevo, 2016, pp:40-46, ISBN: 978-605-83575-0-1 | |
| B.1. N. ALLAHVERDi, G. ALTAN, A fuzzy expert system design to monitor patient’s condition during heart surgery, Proceedings of the 12th International Conference on Computer Systems and Technologies, 2011, DOI:10.1145/2023607.2023664 | |
NATIONAL PROCEEDINGS
| E.6. A. GOKCEN, G.ALTAN, Y. KUTLU, Nonlineer Sınıflandırıcıların Empirical Wavelet Transform Tabanlı Öznitelikler Kullanılarak Solunum Hastalıkları Teşhisi Üzerine Etkisi, International Academic Studies Conference,13-14 Oct 2018, p. 178-185 | |
| E.5. G. ALTAN, Y. KUTLU, A. Ö. PEKMEZCİ & S. NURAL, The Diagnosis of Asthma using Hilbert-Huang Transform and Deep Learning on Lung Sounds, Akıllı Sistemlerde Yenilikler ve Uygulamaları Konferansı (ASYU2017), Antalya, 5-7 Oct. 2017, pp.82 | |
| E.4. G ALTAN, Y KUTLU, Makine Öğrenmesini Kullanarak Solunum Sesinin Analizinin Değerlendirilmesi, XX. Biyomedikal Mühendisliği Ulusal Toplantısı, BİYOMUT’2016, İzmir | |
| E.3. G. ALTAN, Y. KUTLU, ECG based Human identification using Logspace Grid Analysis of Second Order Difference Plot, Signal Processing and Communications Applications Conference (SIU) 2015 23th, Malatya, pp:1288-1291 | |
| E.2. G ALTAN, A YAYIK, Y KUTLU, S YILDIRIM, E YILDIRIM, Konjestif Kalp Yetmezliğinin Hilbert-Huang Dönüşüm ile Analizi, Akıllı Sistemlerde Yenilikler ve Uygulamaları (ASYU2014) Sempozyumu, İzmir, 2014 | |
| E.1. A YAYIK, G ALTAN, Y KUTLU, S YILDIRIM, E YILDIRIM, Görgül Mod Fonksiyonların Eliptik Analizi ile Kongestif Kalp Yetmezliği Teşhisi (Elliptic Analysis of Instinct Mode Functions based CHF Detection), Elektrik, Elektronik, Bilgisayar ve Biyomedikal Mühendisliği Sempozyumu , ELECO 2014, Bursa | |
BOOKS / CHAPTERS
| F.3. G. ALTAN, Enhancing Deep Learning-based Organ Segmentation for Diagnostic Support Systems on Chest X-rays, Deep Learning for Biomedical Applications, Chapter 11, Editors: Utku Kose, Omer Deperlioglu, Jude Hemath, ISBN:978-0-367-42250-9, Press:CRC Press, a member of Taylor & Francis Group, UK. (2021), pp. 255-267, DOI:http://dx.doi.org/10.1201/9780367855611-11 | |
| F.2. G. ALTAN, A Deep Learning Architecture for Identification of Breast Cancer on Mammography by Learning Various Representations of Cancerous Mass, Deep Learning for Cancer Diagnosis, Chapter 10, Editors: Utku Kose, Jafar Alzubi, ISBN:978-981-15-6320-1, DOI: https://doi.org//10.1007/978-981-15-6321-8_10 , Press:Springer (2020), pp. 169-187 | |
| F.1. G. ALTAN, Y. KUTLU, Generalization Performance of Deep Autoencoder kernels for Identification of Abnormalities on Electrocardiograms, Deep Learning for Data Analytics: Foundations, Biomedical Applications, and Challenges, Chapter 3, Editors: Himansu Das, Chittaranjan Pradhan, Nilanjan Dey, ISBN:978-0-12-819764-6, Press:Elsevier (2020), pp.37-62, DOI: https://doi.org/10.1016/B978-0-12-819764-6.00004-1 | |