Document remote-sensing YOLO candidate benchmark

2026-07-07 23:13:36 +02:00
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@@ -107,7 +107,9 @@ This file now starts with the current implementation status. Older preparation/b
 - [x] Add negative/background AOIs to the operator sample corpus and train an expanded local tile-level YOLO candidate.
 - [x] Add a hard-negative model-quality pass with sparse/background AOIs and explicit false-positive scoring.
 - [x] Train a hard-negative-balanced YOLO candidate and rerun dense QA plus background false-positive matrices.
+- [x] Benchmark an external remote-sensing YOLOv8l building candidate as an explicit local model asset.
 - [ ] Find or train a materially stronger aerial/Kempen building model candidate; `geointel-building-yolov8n-expanded160e50-pt` is the best current dense-AOI candidate but still too weak and too noisy for a V1 default.
+- [ ] Train a higher-capacity local aerial-building detector with stronger positive recall while preserving the hard-negative false-positive gate.

 ## Sprint 8 status