Foliage (Neural Network): Difference between revisions
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# Foliage | # Foliage | ||
<gallery widths="200"> | |||
foliage_inference_labels.jpg|[[Labels result type (Inference Overlay)|Labeled features]] on 0.1m satellite image | |||
foliage_inference_scores.jpg|[[Scores result type (Inference Overlay)|Label Scores]] | |||
foliage_inference_masks.jpg|[[Masks result type (Inference Overlay)|Pixel Masks]] | |||
foliage_inference_boxes.jpg|[[Boxes result type (Inference Overlay)|Bounding Boxes]] | |||
</gallery> | |||
{{article end | {{article end | ||
|notes=* | |notes=* | ||
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:
- Foliage
Labeled features on 0.1m satellite image
