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ORCIDArtúr István Károly
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Journal Articles
- 2024
[j2]Artúr István Károly
, Sebestyén Tirczka, Huijun Gao, Imre J. Rudas, Péter Galambos:
Increasing the Robustness of Deep Learning Models for Object Segmentation: A Framework for Blending Automatically Annotated Real and Synthetic Data. IEEE Trans. Cybern. 54(1): 25-38 (2024)- 2021
- [j1]Artúr István Károly, Péter Galambos, Jozsef Kuti, Imre J. Rudas:
Deep Learning in Robotics: Survey on Model Structures and Training Strategies. IEEE Trans. Syst. Man Cybern. Syst. 51(1): 266-279 (2021)
Conference and Workshop Papers
- 2020
- [c4]Takayuki Murooka, Artúr István Károly, Felix von Drigalski, Yoshihisa Ijiri:
Simultaneous Planning of Grasp and Motion using Sample Regions and Gradient-Based Optimization. CASE 2020: 1102-1109 - [c3]Renáta Nagyné Elek, Artúr István Károly, Tamás Haidegger, Péter Galambos:
Towards Optical Flow Ego-motion Compensation for Moving Object Segmentation. ROBOVIS 2020: 114-120 - 2019
- [c2]Artúr István Károly, Márta Takács, Péter Galambos:
OCSVM-based Evaluation Method for Generative Neural Networks. IJCNN 2019: 1-6 - [c1]Artúr István Károly, Renáta Nagyné Elek, Tamás Haidegger, Károly Széll, Péter Galambos:
Optical flow-based segmentation of moving objects for mobile robot navigation using pre-trained deep learning models. SMC 2019: 3080-3086
Coauthor Index
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