| Imitating by generating: Deep generative models for imitation of interactive tasks J Bütepage, A Ghadirzadeh, Ö Öztimur Karadaǧ, M Björkman, D Kragic Frontiers in Robotics and AI 7, 47, 2020 | 33 | 2020 |
| Segmentation fusion for building detection using domain-specific information ÖÖ Karadağ, C Senaras, FTY Vural IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2015 | 24 | 2015 |
| Image segmentation by fusion of low level and domain specific information via Markov Random Fields OO Karadag, FTY Vural Pattern Recognition Letters 46, 75-82, 2014 | 20 | 2014 |
| Experimental assessment of the performance of data augmentation with generative adversarial networks in the image classification problem ÖÖ Karadağ, ÖE Çiçek 2019 Innovations in Intelligent Systems and Applications Conference (ASYU), 1-4, 2019 | 11 | 2019 |
| Evaluation of the robustness of deep features on the change detection problem ÖÖ Karadağ, Ö Erdaş 2018 26Th signal processing and communications applications conference (SIU …, 2018 | 7 | 2018 |
| MRF based image segmentation augmented with domain specific information Ö Öztimur Karadağ, FT Yarman Vural Image Analysis and Processing–ICIAP 2013: 17th International Conference …, 2013 | 5 | 2013 |
| Hanolistic: A hierarchical automatic image annotation system using holistic approach OO Karadag, FTY Vural 2009 IEEE Computer Society Conference on Computer Vision and Pattern …, 2009 | 4 | 2009 |
| Hanolistic: A hierarchical automatic image annotation system using holistic approach O Oztimur, FTY Vural 2008 23rd International Symposium on Computer and Information Sciences, 1-6, 2008 | 4 | 2008 |
| Semantic image segmentation with markov random fields ÖÖ Karadağ, FTY Vural 2012 20th Signal Processing and Communications Applications Conference (SIU …, 2012 | 3 | 2012 |
| Kenar Algılama Algoritmaları Arasında Nesnel Performans Karşılaştırması RE ODUNCUOGLU, OO KARADAG El-Cezeri 9 (4), 1290-1302, 2022 | 2 | 2022 |
| An adversarial framework for open-set human action recognition usingskeleton data ÖÖ KARADAĞ Turkish Journal of Electrical Engineering and Computer Sciences 29 (2), 717-729, 2021 | 2 | 2021 |
| SkelResNet: Transfer learning approach for skeleton-based action recognition U Kılıç, ÖÖ Karadağ, GT Özyer 2024 32nd Signal Processing and Communications Applications Conference (SIU …, 2024 | 1 | 2024 |
| Methods for Trajectory Prediction in Table Tennis MF Kaftanci, M Günay, Ö Öztimur Karadağ Trends in Data Engineering Methods for Intelligent Systems: Proceedings of …, 2021 | 1 | 2021 |
| An MRF framework for co-solving image segmentation and border ownership ÖÖ Karadağ, MA Akkuş, S Kalkan, FTY Vural 2015 23nd Signal Processing and Communications Applications Conference (SIU …, 2015 | 1 | 2015 |
| Fusion of image segmentations under Markov, random fields OO Karadag, FTY Vural 2014 22nd International Conference on Pattern Recognition, 930-935, 2014 | 1 | 2014 |
| Segmentation and decision fusion for building detection OO Karadag, C Senaras, FTY Vural 2014 IEEE Geoscience and Remote Sensing Symposium, 1604-1607, 2014 | 1 | 2014 |
| Integration of domain specific information in the form of color homogeneity into mrf based image segmentation ÖÖ Karadag, FTY Vural Proceedings of the International Conference on Image Processing, Computer …, 2013 | 1 | 2013 |
| Comparison of a Deep Learning and a Hybrid Model for Classification of an Unbalanced Urgent Cases Dataset for Human Faces F Özgür, N Arikan, ÖÖ Karadağ 2024 9th International Conference on Computer Science and Engineering (UBMK …, 2024 | | 2024 |
| SynapSign: an Advanced Machine Learning Framework for American Sign Language Recognition Utilizing a Novel Landmark-Based Dataset ÖÖ Karadağ, İ Balikci, OO KaradaĞ, YK Yüce 2024 Innovations in Intelligent Systems and Applications Conference (ASYU), 1-6, 2024 | | 2024 |
| SkelVIT: consensus of vision transformers for a lightweight skeleton-based action recognition system Ö Öztimur Karadağ Signal, Image and Video Processing 18 (8), 5619-5629, 2024 | | 2024 |
Fatos Tunay Yarman VuralDepartment of Computer Engineering, METUEmail confirmado em ceng.metu.edu.tr
