| _version_ | 1866902238161534976 |
|---|---|
| author | Thota, Sai Krishna Thota |
| author_facet | Thota, Sai Krishna Thota |
| contents | <p>This record contains the supplementary code, derived tables, figures, trained-checkpoint evidence, configuration files, SHA-256 manifests, and reproducibility artifacts for the manuscript “DART-UAV-Lite: Severity-Aware Robustness Evaluation and Degradation-Augmented Repair for UAV Target Detection.”</p> <p>The archive supports UAVDT and VisDrone vehicle-detection robustness experiments, including severity-aware degradation evaluation, clean YOLOv8s reference results, targeted degradation-augmented robust training, external validation, bootstrap confidence intervals, object-scale analysis, qualitative prediction panels, and aggregate manuscript tables/figures.</p> <p>Public dataset archives and raw dataset images are not redistributed. The record contains derived evidence and scripts needed to audit and reproduce the reported results using the public datasets and the accompanying GitHub repository.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_20388601 |
| institution | Zenodo |
| language | eng |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | DART-UAV-Lite V8: Supplementary Code, Tables, and Evidence for UAV Target Detection Robustness Thota, Sai Krishna Thota UAV target detection robustness evaluation visual degradation YOLO UAVDT VisDrone degradation-augmented training <p>This record contains the supplementary code, derived tables, figures, trained-checkpoint evidence, configuration files, SHA-256 manifests, and reproducibility artifacts for the manuscript “DART-UAV-Lite: Severity-Aware Robustness Evaluation and Degradation-Augmented Repair for UAV Target Detection.”</p> <p>The archive supports UAVDT and VisDrone vehicle-detection robustness experiments, including severity-aware degradation evaluation, clean YOLOv8s reference results, targeted degradation-augmented robust training, external validation, bootstrap confidence intervals, object-scale analysis, qualitative prediction panels, and aggregate manuscript tables/figures.</p> <p>Public dataset archives and raw dataset images are not redistributed. The record contains derived evidence and scripts needed to audit and reproduce the reported results using the public datasets and the accompanying GitHub repository.</p> |
| title | DART-UAV-Lite V8: Supplementary Code, Tables, and Evidence for UAV Target Detection Robustness |
| topic | UAV target detection robustness evaluation visual degradation YOLO UAVDT VisDrone degradation-augmented training |
| url | https://doi.org/10.5281/zenodo.20388601 |