https://deeplearning.earth/tags/ssdd/Recent content in Ssdd on DeepLearning.EarthHugo -- gohugo.ioenMon, 28 Sep 2026 06:00:00 +0700https://deeplearning.earth/posts/2026-09-28_ssdd_sar_ship_finetune/Mon, 28 Sep 2026 06:00:00 +0700https://deeplearning.earth/posts/2026-09-28_ssdd_sar_ship_finetune/Optical pretrain, SAR finetune, twelve epochs. SSDD (Zhang et al.) is 1,160 SAR ship chips (~190–688 px), RadarSat-2 / TerraSAR-X / Sentinel-1, 1–15 m. Official split: file numbers whose last digit is 1 or 9 are test (~232); the rest are train (~928). oriented-det v0.3 loads it natively (dataset.format: ssdd). A full Faster R-CNN 1× finetune from the DOTA Hub reached 90.34% mAP50 on held-out test. There is no SSDD Hub zoo.https://deeplearning.earth/posts/2026-09-21_oriented-det_v0_3_0_four_datasets_and_onnx/Mon, 21 Sep 2026 09:00:00 +0700https://deeplearning.earth/posts/2026-09-21_oriented-det_v0_3_0_four_datasets_and_onnx/Three weeks after v0.2.0, Oriented-Det v0.3.1 is on PyPI and tagged on GitHub. This is the dataset + deploy chapter (0.3.0) plus a same-day patch: Rotated RetinaNet Hub is OBB, odet export is a first-class CLI, and deploy sidecars match Hub class lists. The four ResNet-FPN detector families stay. What landed is four native loaders, an HRSC Hub 3× zoo, a DOTA zoo you should advertise from 1×, and ONNX export.