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| Hauptseite > Publikationsdatenbank > Quantum Annealing for Semantic Segmentation in Remote Sensing: Potential and Limitations > print |
| Hauptseite > Publikationsdatenbank > Quantum Annealing for Semantic Segmentation in Remote Sensing: Potential and Limitations > print |
| 001 | 1029393 | ||
| 005 | 20250401102819.0 | ||
| 024 | 7 | _ | |a 10.1109/M2GARSS57310.2024.10537465 |2 doi |
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| 111 | 2 | _ | |a 2024 IEEE Mediterranean and Middle-East Geoscience and Remote Sensing Symposium (M2GARSS) |c Oran |d 2024-04-15 - 2024-04-17 |w Algeria |
| 245 | _ | _ | |a Quantum Annealing for Semantic Segmentation in Remote Sensing: Potential and Limitations |
| 260 | _ | _ | |c 2024 |b IEEE |
| 300 | _ | _ | |a 376-380 |
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| 520 | _ | _ | |a Quantum Annealing (QA) is a powerful method for combinatorial optimisation derived from adiabatic quantum computation. The development of computing devices implementing QA accelerated its adoption in practical use cases. In this paper, we summarise the main features and limitations of QA and its application to remote sensing, specifically to semantic segmentation. We provide indications for successfully applying it to real problems, and techniques for improving its performance. This overview can support practitioners in the adoption of this innovative computing technology. |
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| 773 | _ | _ | |a 10.1109/M2GARSS57310.2024.10537465 |
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