Assoc. Prof. Dr.
- +90 (262) 605 24 09
- Block A2, 252
- Areas of interest
- Machine Learning, Data Fusion, Image/Signal Processing, Hyperspectral Image Processing, Statistical Data Analysis,Biomedical Image Processing, Computer-Aided Diagnosis, Automated Systems.
11.G. Ortac, A.S. Bilgi, K. Tasdemir and H.Kalkan, A hyperspectral imaging based control system for quality assessment of dried figs, Computers and Electronics in Agriculture 130, 38-47 (2016).
10.E. Karacabey, C. Baltacioglu, M. Cevik and H.Kalkan, Optimization of microwave-assisted drying of Jerusalem artichokes (Helianthus tuberosus L.) by response surface methodology and genetic algorithm, Italian Journal of Food Science 28-1, 121-130 (2016).
9.E. Durmus, A. Gunes and H. Kalkan, Detection of Aflatoxin and Surface Mould Contaminated Figs by Using Fourier-Transform Near-Infrared (FT-NIR) Reflectance Spectroscopy, Journal of the Science of Food and Agriculture, (2016).
8.A. Gunes, H. Kalkan and E. Durmus, Optimizing the Color-to-Grayscale Conversion for Image Classification, Signal Image and Video Processing, (2015).
7.H. Kalkan, A. Güneş, E. Durmuş, A.Kuşçu, Non-invasive detection of aflatoxin-contaminated figs using fluorescence and multispectral imaging, Food Additives and Contaminants: Part A,31(8), 1414-1421,2014.
6.H.Kalkan, Online Feature Selection and Classification with Incomplete Data, Turkish Journal of Electrical Engineering; Computer Sciences, 2013, doi:10.3906/elk-1301-181.
5.B.Cetisli, H. Kalkan, Polynomial Curve Fitting with Varying Real Powers, Electronics and Electrical Engineering, 6(112):117-122, 2011.
4.H.Kalkan, P. Beriat, Y. Yardımcı, T. Pearson, Detection of Contaminated Hazelnuts and Ground Red Chili Pepper Flakes by Multispectral Imaging. Computers and Electronics in Agriculture, 77:28-34, 2011.
3.H. Kalkan, F. Ince, A.Tewfik, Y. Yardimci, T. Pearson,Classification of Hazelnut Kernels by Using Impact Acoustic Time- Frequency patterns, EURASIP Journal on Advances in Signal Processing, V: 2008, Article ID 247643.
2.N. Ince, I. Onaran, T. Pearson, A.Tewfik, A. E.Cetin, H.Kalkan, Y.Yardimci, Identification of Damaged Wheat Kernels and Cracked Hazelnuts with Impact Acoustics Time Frequency Patterns,
Transactions of the ASABE, 51(4): 1461-1469, 160; 2008.
1.B.Celasun, E. Mumcuoğlu, H. Kalkan, Sampling of Sentinel Lymph Nodes: A Simulation Study,Quantitative Cytology and Histology, 27:187-194, 2005.
37.U. M. Akkaya and H. Kalkan, "Classification of DNA Sequences with k-mers Based Vector Representations",2021 Innovations in Intelligent Systems and Applications Conference (ASYU), 2021, pp. 1-5.
36.Y. C. Kan and H. Kalkan, "Automatic Detection and Classification of Laser Welding Defects",2021 Innovations in Intelligent Systems and Applications Conference (ASYU), 2021, pp. 1-5, doi: 10.1109/ASYU52992.2021.9599064.
35. B. Kara, H.Kalkan, Cloth Combine Estimation system Using Deep Learning. Innovations in Itelligence Systems and Application Conference (ASYU), Istanbul, Turkey, (2020).
34.H. Kalkan, “Sorting of mycotoxin-contaminated products with hyperspectral imaging”, 2016, 9th Conference of The World Mycotoxin Forum (WMF), Winnipeg, Canada, (2016).
33.Y. E. Gorgulu, H. Kalkan and K. Taşdemir, “Detection of Infected figs by real-time hyperspectral transmittance images”, 2016 International Conference of Agricultural Engineering, Aarhus, Denmark, (2016).
32.A. Güneş, A. S. Bilgi, G. Ortaç, H. Kalkan and K. Taşdemir, “Active Learning Method for Classifying The Mold Contaminated Figs”, 2016 24th Signal Processing and Communication Application Conference (SIU), Zonguldak 1169-1172, (2016).
31.E. Durmuş, A. S. Bilgi, G. Ortaç, H. Kalkan, K. Taşdemir, “Detection of Black Mold Infected Figs by Using Transmittance Spectroscopy”, Proceedings of WHISPERS 2015, 2-5 June, Tokyo, (2015).
30.G Ortaç, K.Taşdemir, A. S. Bilgi, E. Durmuş and H. Kalkan, “A Hyperspectral ImagingSystem for Detection of Dried Figs with Black Mold”, Proceedings of WHISPERS 2015, 2-5,June, Tokyo, (2015).
29.G. Ortaç, A. S. Bilgi, Y. E. Görgülü, A. Güneş, H. Kalkan and K. Taşdemir, “Classification of black mold contaminated figs by hyperspectral imaging”, 2015 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), Abu Dhabi 227-230, (2015).
28.A.S. Bilgi, E. Durmus, H. Kalkan, G. Ortaç and K. Taşdemir, “An automated system for detecting the infected figs by hyperspectral image analysis”, 2015 23th Signal Processing and Communication Application Conference (SIU), Malatya 771-774, (2015).
27.A.Güneş, E. Durmuş, H. Kalkan, A. S. Bilgi, Fusing the RGB Channels of Images for Maximizing the Between Class Distance, Proceedings of ICMV 2014, Milano.
26.E. Durmuş, A. Güneş, H. Kalkan, Surface mold detection on figs using nir spectroscopy and it’s effect on aflatoxin level, Proceedings of IEEE SIU 2014, Trabzon.
25.B. Cetişli, H. Kalkan, A new deterministic validation method for classifier success: Give and Take, Proceedings of IEEE SIU 2014, Trabzon.
24.G. Saygılı, A. S. Bilgi, H. Kalkan, E. A. Hendriks, Confidence-guided adaptive scanline optimization for stereo matching (245), Proceedings of IEEE SIU 2014, Trabzon.
23.A. Günes, H. Kalkan, E. Durmuş, M.B. Büyükcan, Detection Of Aflatoxin Contaminated Figs Using Near-Infrared (NIR) Reflectance Spectroscopy, 2013 ICECCO, Ankara.
22.G. Saygili, C. Balim, H. Kalkan, E. A. Hendriks, Hierarchical Grid-Based Learning Approach for Recovering Unknown Depths in Kinect Depth Maps, International Conference on Image Analysis
and Recognition, Póvoa de Varzim, Portugal, 658-667, Haziran 2013.
21. G. Saygılı,C. Balım, H. Kalkan and E. A. Hendriks, “Hierarchical Grid-Based Learning Approach for Recovering Unknown Depths in Kinect Depth Maps”, Image Analysis and Recognition, Volume 7950 of the series Lecture Notes in Computer Science 658-667, (2013).
20. A. Güneş, E. Durmuş, H. Kalkan, Detection of High Aflatoxin Risk Figs with Computer Vision, IEEE
SIU,(160), KKTC , 2013.
19. G. Saygılı, C. Balım, H. Kalkan, E. A., Hendriks, Estimating the Missing Kinect Depth Information by Polynomial Fitting, IEEE SIU, KKTC, 2013.
18. E. Yenialp,H. Kalkan, Parallel Implementation of Segmentation Algorithms on Graphics Processing Unit. IEEE SIU, KKTC, 2013.
17. H.Kalkan, M. Loog, R.P.W. Duin, and M. Nap, Automated Colorectal Cancer Diagnosis for Whole-Slice Histopathology, MICCAI , Nice, France,550-557, October 2012.
16. H. Kalkan, M. Nap, R.P.W. Duin, and M. Loog, Automated Classification of Local Patches in Colon Histopathology, Proc. of ICPR, Tokyo, Japan, 61-64, Kasım 2012.
15.E.,Yenialp, H., Kalkan, M., Mete, Improving Density Based Clustering with Multi-scale Analysis,
International Conference on Computer Vision and Graphics, ICCVG 2012, Warsay, Poland, 2012.
14. H. Sökün, H. Kalkan, B. Cetişli, Classification of Physical Activities Using Accelerometer Signals, IEEE SIU, Fethiye, 2012.
13. B. Cetişli, H. Kalkan, A New Validation Method For Classification: Give and Take, International Conference of Information Science and Computer Applications, ICISCA, Bali, Indonasia, 2012.
12.H.Kalkan, B.Cetisli, Online Feature Selection and Classification, IEEE International Conference on Acoustics, Speech and Signal Processing, Prag, 2011.
11. B. Cetisli, H. Kalkan, Classiffication Of Multispectral Satallite Images By Using Adaptive Neuro Fuzzy Classifier With Linguistic Hedges, IEEE SIU, Antalya, 2011.
10. H. Kalkan, Ç.Tekinay, Yasemin Yardımcı, Classification of Multispectral Satellite Land Cover Data by 3D Local Discriminant Bases Algorithm, ISCIS 2010, London.
9. H. Kalkan, Yasemin Yardımcı, Extraction of Discriminative Features from Hyperspectral Data, IEEE SSTDM Workshop on International Conference on Data Mining, Pisa, Italy, 2008.
8. H. Kalkan, Y. Yardımcı, Detection of Contaminated Hazelnuts by Hyperspectral Imaging, IEEE SIU, Didim, 2008.
7. H. Kalkan, F. Ince, A. Tewfik ,Y. Yardimci, T. Pearson, Extraction of Optimal Time-Frequency Plane Features for Classification, IEEE SIU, Eskisehir, 2007.
6.Nuri F. Ince ,I. Onaran , A. H. Tewfik , H. Kalkan, T. Pearson, A.E. Cetin, Y.Yardimci, Wheat and Hazelnut Inspection with Impact Acoustics Time-Frequency Patterns, 2007 ASABE Annual International Meeting, Minneapolis.
5. H. Kalkan, M. Özcan, Y. Yardımcı, P. Basaran, P. Beriat, A Novel Prospective Technological Approach: Machine Vision Techniques for Noninvasive Aflatoxin Detection in Chilly Peppers, XII International, IUPAC Symposium on Mycotoxins and Phycotoxins, Istanbul, 2007.
4. H. Kalkan, Y. Yardimci, F. Ince, A. Tewfik, H. Senyuva, M. Arici, T. Pearson, E. Cetin, I. Onaran, Separation of Damaged Shell Hazelnut by Impact Acoustics, XII International IUPAC Symposium on
Mycotoxins and Phycotoxins, Istanbul, 2007.
3.H.Kalkan, Y. Yardımcı, Classification of Hazelnut Kernels by Impact Acoustics, IEEE MLSP, Dublin, 2006.
2. H. Kalkan,Y.Yardımcı, T. Pearson, Wheat Kernel Classification Based on Wavelet Transform and Maximum Likelihood, International Workshop on Sampling Theory and Applications, Samsun, Türkiye, Temmuz 2005.
1. H. Kalkan, Y. Yardımcı, Method Based on Wavelet Transform for Food Safety, IEEE, SIU, Kayseri, 2005.
Yönetilen Doktora Tezleri
1. Betül Kara, Yapay Zeka Temelli Dijital Kombin Sistemi (Devam ediyor)
Yönetilen Yüksek Lisans Tezleri
1. Erdal Yenialp, Histopatolojik Görüntülerin Grafik İşlemci Kullanılarak Bölütlenmesi
2. Ahmet Seçkin Bilgi, Mobil Palatformlar Üzerinden Göz Hastalıkları Takibi
3. Bilal Fedai. Yüz Fiziksel Özellikleri ile Sürücü Yorgunluk Tespiti (Devam ediyor)
- Third Cycle (Doctoral): Information Systems, Middle East Technical University (2008)
- Second Cycle (Master's): Information Systems, Middle East Technical University (2005)
- First Cycle (Undergraduate): Electrical & Electronic Engineering, Ege University (2002)
• European Commission: H2020, “SAFE FOOD AND FEED THROUGH AN INTEGRATED
TOOLBOX FOR MYCOTOXIN MANAGEMENT”, (Partner).
• THE SCIENTIFIC AND TECHNOLOGICAL RESEARCH COUNCIL OF TURKEY (TUBITAK):106E057, “Development of An Automation System for Detecting the Black Mold Infected Figs”, (Coordinator, 2014).
• TUBITAK:110E238, “Automatic Detection of Mold Infected Figs by Multi-Spectral Imaging”, (Coordinator, 2011).
• TUBITAK: Spin off Research Funding:213057, “Optimetry System for Mobile Platforms”, (Coordinator, 2013).
• Turkish Ministry of Science, Industry and Technology Funds: Spin off Research Funding:
1078.TGSD.2015, “Eye Disease Tracking System”, (Counsellor, 2015).
• Turkish Ministry of Science, Industry and Technology Funds: Spin off Research Funding:1149.
TGSD.2015-2, “Simulation System Development for Osteoartrit Patients”, (Counsellor,
• TUBITAK:106E057, “Food Safety with Noninvasive Techniques”, (Researcher, 2006).
• National Science Foundation (NSF) and The Scientific and Technological Research Council of
Turkey (TUBITAK) Cooperation, “Food quality and safety by kernel classification”,