PUBLICATIONS

• O. Strafforello, D. Soydaner, M. Willems, A-S. Maerten, S. De Winter (2024). Have Large Vision-Language Models Mastered Art History?, arXiv preprint arXiv:2409.03521.

• Y. Zhang*, D. Soydaner*, L.  Koßmann, F. Behrad, J. Wagemans (2024). Finding Closure: A Closer Look at the Gestalt Law of Closure in Convolutional Neural Nerworks, arXiv preprint arXiv: 2408.12460.

• O. Strafforello*, G. Muradas Odriozola*, F. Behrad*, L-W. Chen*, A-S. Maerten*, D. Soydaner*, J. Wagemans (2024). BackFlip: The Impact of Local and Global Data Augmentations on Artistic Image Aesthetic Assessment, Vision for art (VISART), Workshop at the European Conference of Computer Vision (ECCV), 30 September, Milan, Italy.

• Y. Zhang, D. Soydaner, F. Behrad, L. Koßmann, J. Wagemans (2024). Investigating the Gestalt Principle of Closure in Deep Convolutional Neural Networks, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), 9-11 October, Bruges, Belgium. 

• D. Soydaner, J. Wagemans (2024). Unveiling the Factors of Aesthetic Preferences with Explainable AI, British Journal of Psychology, 00, 1-35.

• E. Yüksel, D. Soydaner, H. Bahtiyar (2024). Nuclear Mass Predictions using Machine Learning Models, Physical Review C, 109(6), 064322.

• D. Soydaner, J. Wagemans (2024). Multi-Task Convolutional Neural Network for Image Aesthetic Assessment, IEEE Access, 12, 4716-4729.

• A-S. Maerten, D. Soydaner (2023). From Paintbrush to Pixel: A Review of Deep Neural Networks in AI-Generated Art, arXiv preprint arXiv:2302.10913.

• H. Bahtiyar, D. Soydaner,  E. Yüksel (2022). Application of Multilayer Perceptron with Data Augmentation in Nuclear Physics, Applied Soft Computing, 128, 109470.

• D. Soydaner (2022). Attention Mechanism in Neural Networks: Where it Comes and Where it Goes, Neural Computing and Applications, 34, 13371-13385.

• E. Yüksel, D. Soydaner, H. Bahtiyar (2021). Nuclear Binding Energy Predictions Using Neural Networks: Application of the Multilayer Perceptron, International Journal of Modern Physics E, 30(3), 2150017.

• D. Soydaner (2020). Hyper Autoencoders, Neural Processing Letters, 52, 1395-1413.

• D. Soydaner (2020). A Comparison of Optimization Algorithms for Deep Learning, International Journal of Pattern Recognition and Artificial Intelligence, 34(13), 2052013.

• D. Soydaner (2019). Rolling in the Deep Convolutional Neural Networks, International Journal of Intelligent Systems and Applications in Engineering, 7(4), 222-226.

• D. Soydaner,  O. Kocadagli (2015). Artificial Neural Networks with Gradient Learning Algorithm for Credit Scoring, Journal of the School of Business Administration, Istanbul University, 44(2), 3-12. 

CONFERENCE ABSTRACTS

• D. Soydaner, J. Wagemans (2024). Exploring image aesthetics with machine learning: Insights from explainable AI, European Conference on Visual Perception (ECVP), 25-29 August, Aberdeen, Scotland. [Poster]

• D. Soydaner, J. Wagemans (2022). A multi-task learning approach based on convolutional neural networks for image aesthetic evaluation, European Conference on Visual Perception (ECVP), August 28 - September 1, Nijmegen, The Netherlands. [Talk]

• A-S Maerten, D. Soydaner (2022). Art and Machines: A tutorial on AI generated art, The Visual Science of Art Conference (VSAC), August 24-27, Amsterdam, The Netherlands. [Talk]

• J. Wagemans, I. De Vlieghe, C. Bossens, D. Soydaner, C. Damiano, & E. Van Geert (2022). Art Forms in Nature: Perceptual and aesthetic properties of Ernst Haechel's Drawings of New Species, TeaP, March 20-23, Cologne, Germany.

• D. Soydaner, N. Cinemre (2018). Deep Inside the Generative Adversarial Networks, 19th International Symposium on Econometrics, Operations Research and Statistics, October 17-20, Antalya, Turkey. [Talk]

• D. Soydaner (2017). Deep Learning Optimization Algorithms for Image Recognition, 10th International Statistics Congress, December 6-8, Ankara, Turkey. [Talk]

• D. Soydaner, O. Kocadagli (2015). A Hybrid Artificial Neural Network Approach Based Information Criteria for Credit Scoring, 27th European Conference on Operational Research, July 12-15, Glasgow, Scotland, UK. [Talk]

• D. Soydaner (2014). A Hybrid Artificial Neural Network Approach for the Credit Scoring, Young Statisticians' Meeting, July 3-4, Bristol, UK. [Talk]