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2020 – today
- 2024
[j7]Irem Ülkü:
ResLMFFNet: a real-time semantic segmentation network for precision agriculture. J. Real Time Image Process. 21(4): 101 (2024)- [j6]Irem Ülkü
, Ö. Özgür Tanriöver, Erdem Akagündüz:
LoRA-NIR: Low-Rank Adaptation of Vision Transformers for Remote Sensing With Near-Infrared Imagery. IEEE Geosci. Remote. Sens. Lett. 21: 1-5 (2024) - [i2]Irem Ülkü, Ö. Özgür Tanriöver, Erdem Akagündüz:
Near-Infrared and Low-Rank Adaptation of Vision Transformers in Remote Sensing. CoRR abs/2405.17901 (2024) - 2022
- [j5]Irem Ülkü, Erdem Akagündüz:
A Survey on Deep Learning-based Architectures for Semantic Segmentation on 2D Images. Appl. Artif. Intell. 36(1) (2022) - [j4]Irem Ülkü, Erdem Akagündüz, Pedram Ghamisi:
Deep Semantic Segmentation of Trees Using Multispectral Images. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 15: 7589-7604 (2022)
2010 – 2019
- 2019
- [j3]Irem Ülkü, Ersin Kizgut:
Lossy Compressive Sensing Based on Online Dictionary Learning. Comput. Informatics 38(1): 151-172 (2019) - [c1]Irem Ülkü, Panagiotis Barmpoutis, Tania Stathaki, Erdem Akagündüz:
Comparison of single channel indices for U-Net based segmentation of vegetation in satellite images. ICMV 2019: 1143319 - [i1]Irem Ülkü, Erdem Akagündüz:
A Survey on Deep Learning-based Architectures for Semantic Segmentation on 2D images. CoRR abs/1912.10230 (2019) - 2018
- [j2]Irem Ülkü, Ersin Kizgut:
Large-scale hyperspectral image compression via sparse representations based on online learning. Int. J. Appl. Math. Comput. Sci. 28(1): 197-207 (2018) - 2015
- [j1]Irem Ülkü, Behcet Ugur Töreyin:
Sparse coding of hyperspectral imagery using online learning. Signal Image Video Process. 9(4): 959-966 (2015)
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