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@@ -183,14 +183,13 @@ The following illustration gives the resulting confusion matrix :
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  ### Results
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- Samples of results.
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- From test patches with at least 10k points (i.e. at least 4 pts/m²), we sample without cherry-picking, with the following criteria:
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- * (1) WATER & BRIDGE
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- * (2) BUILD_GREENHOUSE
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- * (3) OTHER_PARKING
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- * (4) HIGHSLOPE1
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- * (5) URBAN
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  ---
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@@ -200,12 +199,15 @@ From test patches with at least 10k points (i.e. at least 4 pts/m²), we sample
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  **BibTeX:**
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  ```
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-
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- ```
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-
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-
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- **APA:**
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- ```
 
 
 
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  ```
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  ### Results
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+ From test patches with at least 10k points (i.e. at least 4 pts/m²), we sample without cherry-picking,
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+ to match matches with the following metadata: a) URBAN, b) WATER & BRIDGE, c) OTHER_PARKING, d) BUILD_GREENHOUSE, e) HIGHSLOPE.
 
 
 
 
 
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+ <div style="position: relative; text-align: center;">
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+ <p style="margin: 0;">Input point cloud, target classification, and model prediction for a subset of patches from the test set of FRACTAL.</p>
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+ <img src="FRACTAL-LidarHD_7cl_randlanet-sample_predictions.excalidraw.png" alt="Sample input pc, target, and predictions" style="width: 70%; display: block; margin: 0 auto;"/>
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+ </div>
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  ---
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  **BibTeX:**
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  ```
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+ @misc{gaydon2024pureforest,
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+ title={TBD},
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+ author={Charles Gaydon and Michel Daab and Floryne Roche},
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+ year={2024},
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+ eprint={TBD},
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+ archivePrefix={arXiv},
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+ url={TBD}
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+ primaryClass={cs.CV}
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+ }
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  ```
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