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Quantum Annealing for Semantic Segmentation in Remote Sensing: Potential and Limitations

Year: 2024

Type: conference-paper

Abstract: Quantum Annealing (QA) is a powerful method for combinatorial optimization derived from adiabatic quantum computation. The development of computing devices implementing QA accelerated its adoption in practical use cases. In this paper, we summarize 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.

Source: IEEE Mediterranean and Middle-East Geoscience and Remote Sensing Symposium (M2GARSS)

DOI: 10.1109/m2garss57310.2024.10537465

Authors: Amer Delilbasic, Bertrand Le Saux, Morris Riedel, Kristel Michielsen, Gabriele Cavallaro

Institutions: University of Iceland, Forschungszentrum Jülich, Jülich Supercomputing Centre, European Space Agency, European Space Research Institute

Language: English

Topic: Quantum Computing Algorithms and Architecture

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W4399039547

FWCI: 0.577

Cites: 25

Cited by: 2

Related to: 10