aerial-lidar-spatial-eval
Fuente:
Zenodo
Salvato in:
| Autore principale: | |
|---|---|
| Natura: | Recurso digital |
| Pubblicazione: |
Zenodo
2026
|
| Soggetti: | |
| Accesso online: | |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866901556093255680 |
|---|---|
| author | Muhammad Daud |
| author_facet | Muhammad Daud |
| contents | <p><strong>aerial-lidar-spatial-eval</strong> provides distance-weighted, spatially aware evaluation metrics for aerial LiDAR semantic-segmentation outputs.</p> <p>The project focuses on metrics that are more diagnostic than a single global score, including boundary-aware intersection-over-union and hard-point detection for areas where model predictions are spatially fragile.</p> <p>It is intended for comparing segmentation experiments, communicating where model performance breaks down, and supporting QA workflows for LiDAR-derived classification products in browser-based or Python-backed analysis environments.</p> <p>Archived source repository: <a href="https://github.com/daudee215/aerial-lidar-spatial-eval">https://github.com/daudee215/aerial-lidar-spatial-eval</a></p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_19856560 |
| institution | Zenodo |
| language | |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | aerial-lidar-spatial-eval Muhammad Daud GIS LiDAR semantic segmentation evaluation metrics spatial QA boundary-aware IoU Python Pyodide <p><strong>aerial-lidar-spatial-eval</strong> provides distance-weighted, spatially aware evaluation metrics for aerial LiDAR semantic-segmentation outputs.</p> <p>The project focuses on metrics that are more diagnostic than a single global score, including boundary-aware intersection-over-union and hard-point detection for areas where model predictions are spatially fragile.</p> <p>It is intended for comparing segmentation experiments, communicating where model performance breaks down, and supporting QA workflows for LiDAR-derived classification products in browser-based or Python-backed analysis environments.</p> <p>Archived source repository: <a href="https://github.com/daudee215/aerial-lidar-spatial-eval">https://github.com/daudee215/aerial-lidar-spatial-eval</a></p> |
| title | aerial-lidar-spatial-eval |
| topic | GIS LiDAR semantic segmentation evaluation metrics spatial QA boundary-aware IoU Python Pyodide |
| url | https://doi.org/10.5281/zenodo.19856560 |