NUH ALPASLAN

Doç. Dr. NUH ALPASLAN

Unvan : DOÇENT

Birim / Bölüm : MÜHENDİSLİK-MİMARLIK FAKÜLTESİ / BİLGİSAYAR MÜHENDİSLİĞİ

Email : nalpaslan@bingol.edu.tr

Dahili : 1934

Oda No : D212


  Nuh ALPASLAN, PhD

Nuh ALPASLAN received his B.S. degree in Computer Engineering from Firat University, Elaziğ, Turkey in 2010. He received both his M.S. (2013) and Ph.D.(2017) degrees in Computer Engineering from The Inonu University, Malatya, Turkey. He has also been in the USA as visiting research scholar for his doctoral studies. His research has involved the areas of medical image analysis, machine learning, plant precision agriculture using image processing and machine vision applications.  Dr. Alpaslan joined School of Engineering and Architecture at the University of Bingol in January 2018.

e-mail:  nuhalpaslan@gmail.com                 

                                                   

PhD, Inonu University, Graduate School of Natural and Applied SciencesDepartment of Computer Science, 2017

 Thesis Topic: A decision support system based on content-based image retrieval for breast cancer diagnosis.

Advisor: Prof. Dr. Prabir Bhattacharya and Assoc. Prof. Dr. Davut HANBAY

MSc, Inonu University, Graduate School of Natural and Applied SciencesDepartment of Computer Science, 2013

Thesis Topic: New approaches to gradient-based heterogeneous feature extraction methods.

Advisor: Assoc. Prof. Dr. M. Fatih TALU

BSc, Firat University, School of Engineering, Department of Computer Science, 2010. 

Job Title

Institution

Year

Research Assistant

Bingol University(Bingol, Turkey)

   2010-2011

Research Assistant

Inonu University(Malatya, Turkey) 

2011-2017

Asst. Prof. Dr.

Bingol University​(Bingol, Turkey) 

       2018 - 2020

Assoc. Prof. Dr.

Bingol University​(Bingol, Turkey) 

2020 - 

 

Job Title

Institution

Year

Visiting Research Scholar

Morgan State University   (Maryland, USA) 

2015-2016

Visiting Research Scholar

Johns Hopkins University (Maryland, USA) 

    2016

 

A.1.  N. Alpaslan and K. Hanbay, “Multi-scale shape index-based local binary patterns for texture classification,” IEEE Signal Process. Lett., vol. 27, pp. 660–664, Apr. 2020, doi: 10.1109/lsp.2020.2987474.

A.2.  N. Alpaslan and K. Hanbay, "Multi-Resolution Intrinsic Texture Geometry-Based Local Binary Pattern for Texture Classification," in IEEE Access, vol. 8, pp. 54415-54430, 2020.

A.3  Alpaslan, Nuh. "A Finite Difference Approximate Fractional-Order Gradient Operator for Improving Image Classification Performance." Journal of Control Engineering and Applied Informatics 22, no. 1 (2020): 3-13.

A.4. Fırat, Hüseyin, Nuh Alpaslan, and Davut Hanbay. "Dikdörtgen Parçalar ile İki Boyutlu Kesme ve Paketleme Problemi için Sezgisel Yöntemler Kullanılan Bir Hibrit Metodoloji." Politeknik Dergisi 22.4: 979-988.

A.5 Hanbay K.,Alpaslan, N.,Talu M. F.,Hanbay D.,Karcı A.,Kocamaz A. F., Continuous rotation invariant features for gradient based texture classification.  Computer Vision and Image Understanding, 132, 87-101, 2015. 

A.6. Hanbay K., Alpaslan N., Talu, M.F., Hanbay D, “Principal curvatures based rotation invariant algorithms for efficient texture classification”, Neurocomputing, Volume 199, 26 July 2016, Pages 77-89, ISSN 0925-2312.

A.7. Talu, M.F., Gül, M., Alpaslan, N., Yigitcan, B., "Calculation Of Melatonin And Resveratrol Effects On Steatosis Hepatis Using Soft Computing Methods", Computer Methods and Programs in Biomedicine, Volume 111, Issue 2, August 2013, Pages 498–506.

 

B1. Alpaslan, N. (2020). A Novel Texture Classification Method Based on Neutrosophic Truth. Sakarya University Journal of Computer and Information Sciences, 3 (1), 28-39. DOI: 10.35377/saucis.03.01.709186.

B.2. ŞAHİN, N , ALPASLAN, N . (2020). SegNet Mimarisi Kullanılarak Cilt Lezyon Bölütleme Performansının İyileştirilmesi. Avrupa Bilim ve Teknoloji Dergisi , () , 40-45 . DOI: 10.31590/ejosat.araconf6

B.3. Alpaslan, Nuh. "Renkli görüntülerde kenar yönelimlerini belirlemek için iyileştirilmiş yöntem." Türk Doğa ve Fen Dergisi 7.1: 29-34.

B.4. Fırat, Hüseyin, and Nuh ALPASLAN. "Sezgisel Algoritmalar Kullanılarak İki Boyutlu Dikdörtgen Şerit Paketleme Probleminin Çözümü." Avrupa Bilim ve Teknoloji Dergisi 17: 315-322.

B.5. ALPASLAN, N. (2019). MEME KANSERİ TANISI İÇİN DERİN ÖZNİTELİK TABANLI KARAR DESTEK SİSTEMİ. Selçuk Üniversitesi Mühendislik, Bilim Ve Teknoloji Dergisi7(1), 213-227.

B.6. Alpaslan, N., Talu, M.F., Gül, M., Yiğitcan, B., "Calculation of drug effectiveness on treatment of steatosıs hepatis Using HOG based ANN. ", Sakarya University Journal of Science, [S.l.], v. 16, n. 2, jun. 2012.

C.1. Alpaslan, N.,  “A Deep Feature Based Decision Support System for Breast Cancer Diagnosis”, I. Uluslararası Bilimsel ve Mesleki Çalışmalar Kongresi, 5-8 Ekim 2017, Nevşehir, Türkiye.

C.2. Alpaslan, N.,  Rahman M.,  “An Integrated Classification and Retrieval Based Diagnostic Aid for Breast Cancer Detection of Mammograms”,  SIIM Scientific Conference on Machine Intelligence in Medical Imaging, September 12-13, 2016, Alexandria / Virginia, USA.

C.3. Alpaslan, N.,  Rahman M.,  “Developing a Decision Support System for Breast Cancer Detection on Mammograms using Image Processing   Machine Learning”,  XSEDE16 Conference on Diversity, Big Data, and Science at Scale, July 17-21, 2016, Miami / Florida, USA.     

C.4. Alpaslan, N.,  Rahman M.,  “Mammogram classification assisted by content based image retrieval for breast cancer diagnosis”, 23rd Annual Undergraduate and Graduate Research Symposium,  April 14, 2016, Baltimore / Maryland, USA.

C.5. Alpaslan, N., İmik Ö.,Hanbay D., “Breast mass classification in mammogram images based on wavelet transform”, International conference on natural science and engineering, March 2016, pp. 1469-1472, Kilis, Türkiye.

C.6. Alpaslan, N.,  “A Decision Support System  DSS  for Breast Cancer Detection Based on Automated Mass Detection  Classification  and Retrieval of Mammograms”.  Morgan Innovation Day, March 15, 2016, Annapolis / Maryland, USA.     

C.7. Rahman M., Alpaslan, N.,  “Automated Melanoma Recognition in Dermoscopic Images Based on Extreme Learning Machine (ELM)”,  SPIE Medical Imaging,  March 3, 2017, Orlando / Florida, USA.

C.8. Alpaslan, N.,  Rahman M.,  “Developing a Retrieval Based  Diagnostic Aid  for Automated Melanoma Recognition of Dermoscopic Images”, IEEE Applied Imagery Pattern Recognition workshop (AIPR2016), October 18-20, 2016, Washington DC, USA.

C.9. Alpaslan, N.,  “A Novel Feature Extraction Method Based on Color Gradient”,  I. Uluslararası Bilimsel ve Mesleki Çalışmalar Kongresi, 5-8 Ekim 2017, Nevşehir, Türkiye.

C.10. Alpaslan, N., Hanbay, K., Hanbay, D. and Talu, M.F., “Continuous rotation invariant texture classification based on CoHOG algorithm”, Third International Eurasian Conference on Mathematical Sciences and Applications, August 25-28, 2014, Vienna,  Austria.

C.11. Alpaslan, N., Turhan M.M., Hanbay D., “Determining noise performance of co-occurrence GMuLBP on object detection task”, Sixth International Conference on Machine Vision (ICMV), December 24, 2013, London, United Kingdom.

 

D.1. Alpaslan, N., Hanbay D., Kara A.,Zencir B., “Classification of breast masses in mammogram images using KNN”,  23nd Signal Processing and Communications Applications Conference (SIU), 16- May 19 2015, pp. 1469-1472, Malatya, Turkey.

D.2. Alpaslan N., Toptaş M., Öztürk B., Hanbay D., "Mass Detection on Mammograms and Normal-Benign-Malignant Distinction", National Conference on biomedical Technologies(TıpTekno), September 25-27, 2014, Kapadokya / Turkey.

D.3. Arı A., Alpaslan, N., Hanbay D.,  “Computer aided tumor detection system using brain MR images”,  Medical Technologies National Conference (TIPTEKNO), 15-18 Ekim 2015, pp. 1-4, Bodrum, Türkiye.

D.4.      Alpaslan, N., Hanbay, K., Hanbay, D. and Talu, M.F., “A novel texture classifıcation method based on hessian matrix and principal curvatures”, 22nd Signal Processing and Communications Applications Conference (SIU), pp.160,163, 23-25 April 2014, Trabzon, Turkey.

D.5.    Alpaslan, N., Talu, M.F., Gül, M., "Parametric and non-parametric clustering for segmentation of mitochondrial damage in cardiac cells", International Symposium on Biomedical Science and Technology (BIOMED), p.38, November 23-25, 2011, Ankara / Turkey.

D.6. Sulu M.,Ince K.,Alpaslan N.,Boy O.,Karcı A.,Icen I.," Pattern Discovery in graph-based biological sequence", Fırat University Symposium on Electrical- Electronics and Computer Systems FEEB, October 5-7, 2011, Elazığ / Turkey.

 

Rahman, M., Alpaslan, N. (2017). A Decision Support System (DSS) for Breast Cancer Detection Based on Invariant Feature Extraction, Classification, and Retrieval of Masses of Mammographic Images. Medical Imaging and Image-Guided Interventions (s. 11-32). London: IntechOpen Limited.

En İyi Makale Ödülü: Developing a Decision Support System for Breast Cancer Detection on Mammograms using Image Processing Machine Learning, "XSEDE16 Conference on Diversity, Big Data, and Science at Scale",   Miami, Florida, Amerika Birleşik Devletleri, 2016