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Ground Truth in Classification Accuracy Assessment: Myth and Reality

The ground reference dataset used in the assessment of classification accuracy is typically assumed implicitly to be perfect (i.e., 100% correct and representing ground truth). Rarely is this assumption valid, and errors in the ground dataset can cause the apparent accuracy of a classification to di...

Deskribapen osoa

Gorde:
Xehetasun bibliografikoak
Egile nagusia: Giles M. Foody
Formatua: Artigo
Hizkuntza:Inglês
Argitaratua: MDPI AG 2024-02-01
Saila:Geomatics
Gaiak:
Sarrera elektronikoa:https://www.mdpi.com/2673-7418/4/1/5
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