Innovative Artificial Intelligence Applications in Pharmacology Research

Our group conducts research that develops new solutions using artificial intelligence and data science in order to improve and accelerate traditional pharmacology methods. These researches are carried out by experts in the fields of artificial intelligence, deep learning, data analytics, image processing and pharmacology. 

Recent Publications

Kan Hücrelerinin Optimum Odaklı Görüntülenmesi için Derin Öğrenme Tabanlı Yaklaşımın Geliştirilmesi

DOĞU F. T., Danaei Z., DOĞAN H., DOĞAN R. Ö., SEZEN F. S.
KSÜ Mühendislik Bilimleri Dergisi, vol.27, no.4, pp.1465-1476, 2024 (Peer-Reviewed Journal)

Extracting 3D Structure of Blood Cells Using Shape From Focus Strategies

DOĞU F. T., DOĞAN H., DOĞAN R. Ö., AY İ., SEZEN F. S.
2024 Innovations in Intelligent Systems and Applications Conference (ASYU, Ankara, Turkey, 16 October 2024

Performance Improvement in Blood Cell Segmentation with Deep Learning-based Image Fusion Approach

Doğu F. T., Doğan H., Doğan R. Ö., Sezen F. S.
8th International Artificial Intelligence and Data Processing Symposium (IDAP’24), Malatya, Turkey, 21 - 22 September 2024, pp.1-6

DL-EDOF: Novel Multi-Focus Image Data Set and Deep Learning-Based Approach for More Accurate and Specimen-Free Extended Depth of Focus

Doğan H., Doğan R. Ö., Ay İ., Sezen F. S.
Journal of Imaging Informatics in Medicine, vol.1, no.37, pp.1991-2013, 2024 (SCI-Expanded)

An Efficient Technique based on Deep Learning for Automatic Focusing in Microscopic System

Doğu F. T., Doğan H., Doğan R. Ö., Ay İ., Sezen F. S.
2nd INTERNATIONAL CONGRESS of ELECTRICAL and COMPUTER ENGINEERING, Balıkesir, Turkey, 22 - 25 November 2023, pp.1-6

INVESTIGATION OF EFFECTS OF DEEP FEATURES ON FOCUS VALUES EXTRACTION IN EXTENDED DEPTH OF FOCUS

Danışmaz S., Emir S. N., Doğan H., Doğan R. Ö.
Eskişehir Osmangazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, vol.31, no.3, pp.917-930, 2023 (Peer-Reviewed Journal)

A higher performance shape from focus strategy based on unsupervised deep learning for 3D shape reconstruction

DOĞAN H.
Multimedia Tools and Applications, vol.83, no.12, pp.35825-35848, 2024 (SCI-Expanded)

Floresan Mikroskop Sistemlerinde Yüksek Doğruluklu Nükleer Segmentasyonu için Otomatik Kodlayıcı Tabanlı Modellerin Geliştirilmesi

Emir S. N., Danışmaz S., DOĞAN H., DOĞAN R. Ö.
Karadeniz Fen Bilimleri Dergisi, vol.13, no.3, pp.801-813, 2023 (Peer-Reviewed Journal)

Deep Learning Based Focus Measurement Operator for 3D Imaging in Microscopic Systems

Doğan H., Doğan R. Ö.
31. IEEE Sinyal İşleme ve İletişim Uygulamaları Kurultayı, İstanbul, Turkey, 5 - 08 July 2023, pp.1-4

An Extensive Study: Creation of A New Inverted Microscope Image Data Set and Improving Auto-Encoder Models for Higher Accuracy Segmentation of HaCaT Cell Culture Line

Sevim Z., DOĞAN H., DEMİR ÖKSÜZ Z., SEZEN F. S., DOĞAN R. Ö.
5th International Congress on Human-Computer Interaction, Optimization and Robotic Applications, 08 June 2023, pp.1-6