The DOI matches its Crossref record; 6 of the 7 references it cites were found in a registry or an index.
Multi-Spectral Image Classification with Quantum Neural Network
Abstract
Processing Earth observation images to obtain land cover classification is an important task allowing to track changes on the Earth's surface resulting from natural processes, human activity, and climate change. The amount of data acquired from Earth observation satellites is very large and their processing takes large amount of computational resources. We investigate application of quantum circuit based neural network classifiers for multi-spectral data classification aimed at obtaining the land cover information. We show a proof-of-concept of our approach.
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“It is worth to highlight that only very few works have addressed the application of quantum machine learning (QML) to remote sensing in the current state of the art.”
From On Circuit-Based Hybrid Quantum Neural Networks for Remote Sensing Imagery Classification (2022) · cites this paper as [24]
Citations
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Metadata
- Authors
- Gawron, P., & Lewinski, S.
- Affiliations
- Nicolaus Copernicus Astronomical Center (PL)
- Space Research Center, Polish Academy of Sciences,Warsaw,Poland,00-716
- ORCID
- Gawron, Piotr
- Venue
- IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium
- Publisher
- IEEE
- Published
- 2020-09-26
- Pages
- 3513-3516
- OpenAlex
- W3131862063
- Cited by
- 42
- References
- 7
- Citations by year
- 2026: 6 · 2025: 6 · 2024: 9 · 2023: 13 · 2022: 6 · 2021: 2
- FWCI
- 2.00
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE International Geoscience and Remote Sensing Symposium (IGARSS) (publishedVersion)
- Funders
- ERDF
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Quantum Computing Algorithms and Architecture
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Remote-Sensing Image Classification
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
- Keywords
- quantum neural networks, land cover classification, Earth observation images, satellite imagery, quantum machine learning
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