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ORCIDÖzge Öztimur Karadag
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2020 – today
- 2024
[j5]Özge Öztimur Karadag:
SkelVIT: consensus of vision transformers for a lightweight skeleton-based action recognition system. Signal Image Video Process. 18(8-9): 5619-5629 (2024)- [c10]Ahmet Sezer Akdeniz, Berkan Özgür, Emre Sahin, Özge Öztimur Karadag, Özlem Ceren Günizi:
Comparative Analysis of Vision Transformers and Morphological Approaches for Ki-67 Index Estimation on Histopathologic Images: An Experimental Evaluation. SIU 2024: 1-4 - [c9]Ugur Kiliç, Özge Öztimur Karadag, Gülsah Tümüklü Özyer:
SkelResNet: Transfer Learning Approach for Skeleton-Based Action Recognition. SIU 2024: 1-4 - 2023
- [i2]Özge Öztimur Karadag:
Act-VIT: A Representationally Robust Attention Architecture for Skeleton Based Action Recognition Using Vision Transformer. CoRR abs/2311.08094 (2023) - 2021
- [j4]Özge Öztimur Karadag
:
An adversarial framework for open-set human action recognition using skeleton data. Turkish J. Electr. Eng. Comput. Sci. 29(2): 717-729 (2021) - [c8]Rahmani Saygin, Özge Öztimur Karadag:
An Evaluation of the Layers of a Deep Network on the Optical Character Recognition Problem. SIU 2021: 1-4 - 2020
- [j3]Judith Bütepage, Ali Ghadirzadeh, Özge Öztimur Karadag, Mårten Björkman, Danica Kragic:
Imitating by Generating: Deep Generative Models for Imitation of Interactive Tasks. Frontiers Robotics AI 7: 47 (2020)
2010 – 2019
- 2019
- [i1]Judith Bütepage, Ali Ghadirzadeh, Özge Öztimur Karadag, Mårten Björkman, Danica Kragic:
Imitating by generating: deep generative models for imitation of interactive tasks. CoRR abs/1910.06031 (2019) - 2018
- [c7]Özge Öztimur Karadag, Ozlem Erdas:
Evaluation of the robustness of deep features on the change detection problem. SIU 2018: 1-4 - 2015
- [j2]Özge Öztimur Karadag, Çaglar Senaras, Fatos T. Yarman-Vural:
Segmentation Fusion for Building Detection Using Domain-Specific Information. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 8(7): 3305-3315 (2015) - [c6]Özge Öztimur Karadag, Mehmet Akif Akkus, Sinan Kalkan, Fatos T. Yarman-Vural:
An MRF framework for co-solving image segmentation and border ownership. SIU 2015: 839-842 - 2014
- [b1]Özge Öztimur Karadag:
Fusion of image segmentation with domain specific information under an unsupervised markov random fields model ; Markov rasgele alanları aracılığı ile anlam bilgisi ve imge bölütlemenin birleştirilmesi. Middle East Technical University, Çankaya, Ankara, Turkey, 2014 - [j1]Özge Öztimur Karadag, Fatos T. Yarman-Vural:
Image segmentation by fusion of low level and domain specific information via Markov Random Fields. Pattern Recognit. Lett. 46: 75-82 (2014) - [c5]Özge Öztimur Karadag, Fatos T. Yarman-Vural:
Fusion of Image Segmentations under Markov, Random Fields. ICPR 2014: 930-935 - [c4]Özge Öztimur Karadag, Çaglar Senaras, Fatos T. Yarman-Vural:
Segmentation and decision fusion for building detection. IGARSS 2014: 1604-1607 - 2013
- [c3]Özge Öztimur Karadag, Fatos T. Yarman-Vural:
MRF Based Image Segmentation Augmented with Domain Specific Information. ICIAP (2) 2013: 61-70 - 2012
- [c2]Özge Öztimur Karadag, Fatos T. Yarman-Vural:
Semantic image segmentation with Markov Random Fields. SIU 2012: 1-4
2000 – 2009
- 2009
- [c1]Özge Öztimur Karadag, Fatos T. Yarman-Vural:
HANOLISTIC: A Hierarchical Automatic Image Annotation System Using Holistic Approach. CVPR Workshops 2009: 16-21
Coauthor Index
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