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QADI as a New Method and Alternative to Kappa for Accuracy Assessment of Remote Sensing-Based Image Classification
2022
Sensors
Classification is a very common image processing task. The accuracy of the classified map is typically assessed through a comparison with real-world situations or with available reference data to estimate the reliability of the classification results. Common accuracy assessment approaches are based on an error matrix and provide a measure for the overall accuracy. A frequently used index is the Kappa index. As the Kappa index has increasingly been criticized, various alternative measures have
doi:10.3390/s22124506
pmid:35746285
pmcid:PMC9230807
fatcat:pdnkp7aaevhkniopeihi6v5yq4