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Quantitative assessment of soil salinity using multi-source remote sensing data based on the support vector machine and artificial neural network
Research article (International Journal of Remote Sensing, 2018) · cited 103× · AI/ML
Quantitative assessment of soil salinity using multi-source remote sensing data based on the support vector machine and artificial neural network
Summary
Quantitative assessment of soil salinity using multi-source remote sensing data based on the support vector machine and artificial neural network is a scholarly article[1].
Key Facts
Quantitative assessment of soil salinity using multi-source remote sensing data based on the support vector machine and artificial neural network's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). Quantitative assessment of soil salinity using multi-source remote sensing data based on the support vector machine and artificial neural network. Retrieved May 24, 2026, from https://4ort.xyz/entity/quantitative-assessment-of-soil-salinity-using-multi-source-remote-sensing-data-based-on-the-support-vector-machine-and-
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BibTeX@misc{4ortxyz_quantitative-assessment-of-soil-salinity-using-multi-source-remote-sensing-data-based-on-the-support-vector-machine-and-_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Quantitative assessment of soil salinity using multi-source remote sensing data based on the support vector machine and artificial neural network}}, year = {2026}, url = {https://4ort.xyz/entity/quantitative-assessment-of-soil-salinity-using-multi-source-remote-sensing-data-based-on-the-support-vector-machine-and-}, note = {Accessed: 2026-05-24}}
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