A Comparison of Optimization Algorithms for Deep Learning D Soydaner International Journal of Pattern Recognition and Artificial Intelligence, 2020 | 267 | 2020 |
Attention mechanism in neural networks: where it comes and where it goes D Soydaner Neural Computing and Applications 34 (16), 13371-13385, 2022 | 180 | 2022 |
From paintbrush to pixel: A review of deep neural networks in AI-generated art AS Maerten, D Soydaner arXiv preprint arXiv:2302.10913, 2023 | 38 | 2023 |
Nuclear binding energy predictions using neural networks: Application of the multilayer perceptron E Yüksel, D Soydaner, H Bahtiyar International Journal of Modern Physics E 30 (03), 2150017, 2021 | 32 | 2021 |
Artificial neural networks with gradient learning algorithm for credit scoring D Soydaner, O Kocadağlı İstanbul Üniversitesi İşletme Fakültesi Dergisi 44 (2), 3-12, 2015 | 14 | 2015 |
Application of multilayer perceptron with data augmentation in nuclear physics H Bahtiyar, D Soydaner, E Yüksel Applied Soft Computing 128, 109470, 2022 | 9 | 2022 |
Nuclear mass predictions using machine learning models E Yüksel, D Soydaner, H Bahtiyar Physical Review C 109 (6), 064322, 2024 | 8 | 2024 |
Multi-task convolutional neural network for image aesthetic assessment D Soydaner, J Wagemans Ieee Access 12, 4716-4729, 2024 | 7 | 2024 |
Hyper Autoencoders D Soydaner Neural Processing Letters 52 (2), 1395-1413, 2020 | 4 | 2020 |
Rolling in the deep convolutional neural networks D Soydaner International Journal of Intelligent Systems and Applications in Engineering, 2019 | 3* | 2019 |
Investigating the Gestalt Principle of Closure in Deep Convolutional Neural Networks Y Zhang, D Soydaner, F Behrad, L Koßmann, J Wagemans arXiv preprint arXiv:2411.00627, 2024 | 2 | 2024 |
Training deep neural network based hyper autoencoders with machine learning methods D Soydaner PhD dissertation, Mimar Sinan Fine Arts University, Institute of Science and …, 2018 | 2 | 2018 |
Finding Closure: A Closer Look at the Gestalt Law of Closure in Convolutional Neural Networks Y Zhang, D Soydaner, L Koßmann, F Behrad, J Wagemans arXiv preprint arXiv:2408.12460, 2024 | 1 | 2024 |
Unveiling the factors of aesthetic preferences with explainable AI D Soydaner, J Wagemans British Journal of Psychology, 2024 | 1 | 2024 |
Have Large Vision-Language Models Mastered Art History? O Strafforello, D Soydaner, M Willems, AS Maerten, S De Winter arXiv preprint arXiv:2409.03521, 2024 | | 2024 |
BackFlip: The Impact of Local and Global Data Augmentations on Artistic Image Aesthetic Assessment O Strafforello, GM Odriozola, F Behrad, LW Chen, AS Maerten, ... arXiv preprint arXiv:2408.14173, 2024 | | 2024 |
A multi-task learning approach based on convolutional neural networks for image aesthetic evaluation D Soydaner, J Wagemans Perception 51, 168-168, 2022 | | 2022 |
Art forms in nature: perceptual and aesthetic properties of Ernst Haeckel's drawings of new species J Wagemans, I De Vlieghe, C Bossens, D Soydaner, C Damiano, ... TeaP (Tagung experimentell arbeitender Psycholog: innen; Conference of …, 2022 | | 2022 |
Derin sinir ağı temelli üst özkodlayıcıların yapay öğrenme yöntemleriyle eğitilmesi (Training deep neural network based hyper autoencoders with machine learning methods) D Soydaner Mimar Sinan Güzel Sanatlar University, Turkey, 2018 | | 2018 |
Derin sinir ağı temelli üst özkodlayıcıların yapay öğrenme yöntemleriyle eğitilmesi D Soydaner Mimar Sinan Güzel Sanatlar Üniversitesi, 2018 | | 2018 |