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However, traditional satellite-based and raster classifications rely on pixels that are assigned to a single category and often generalized.
Supervised and unsupervised classifications rely on classical set theory in assigning pixels into discrete classes based on training sets and some statistically determined criteria.
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Older classifications relied on the Ural Mountains stratigraphy.
Most Machine Learning (ML) methods, from clustering to classification, rely on a distance function to describe relationships between datapoints.
Both biological classification and folkbiological classification rely on direct contact and experience with plants and animals in the natural environment (Medin and Atran 1999).
First, the results of behavior classification rely on the RT thresholds and are not meaningful unless the identified thresholds are validated.
The classification relies on the analysis of the eigenvalues of the transfer matrix for a unit-cell and the asymptotics derived for the transmission coefficient.
The classification relies on the motion pattern attributes associated with the trajectories of each road-user type, namely, vehicles, pedestrians and cyclists.
In 2013, five new distinct epithelial tumors and three provisional entities have been added to this classification, relying on morphology, immunohistochemistry, cytogenetics, and molecular pathology advances.
In principle, we would imagine that the classification relies on the visual content surrounding the keypoints.
However, this requires the objects to be detected to possess a sufficient amount of well separating features as classification relies on many cascaded stages containing several image features.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com