Foliage (Neural Network): Difference between revisions

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{{article end
{{article end
|notes=*
|notes=*
|howtos=*[[]]
|howtos=
 
*[[How to detect foliage using an Inference Overlay]]
*[[How to create foliage height areas based on an Inference Overlay]]
|seealso=*[[Inference Overlay]]
|seealso=*[[Inference Overlay]]
*[[Foliage areas (Heat Overlay)]]
*[[Foliage areas (Heat Overlay)]]
}}
}}

Revision as of 08:44, 16 October 2024

The Foliage Neural Network is a Convolution Neural Network that identifies foliage of individual trees and bushes, mainly for gardens and private property. This Neural Network is not suited for identifying individual trees within forested areas.

An Inference Overlay can be configured with this Neural Network. Its default settings are:

Preferred grid cell size: 0.1m
Inference mode: BBox Detection
Mask threshold:
Score threshold:
Stride fraction: 0.50 (50%)

Identifiable features:

  1. Foliage