From 0eb432a2401f776e43768379af37f70a0c31a09a Mon Sep 17 00:00:00 2001 From: yawenzzzz Date: Thu, 16 Jan 2025 23:59:57 +0000 Subject: [PATCH] resolve comments --- docs/landsat_vessels.md | 38 +++++++++++++++++++++++++++++++------- 1 file changed, 31 insertions(+), 7 deletions(-) diff --git a/docs/landsat_vessels.md b/docs/landsat_vessels.md index 37dda17..27d6e3a 100644 --- a/docs/landsat_vessels.md +++ b/docs/landsat_vessels.md @@ -5,7 +5,7 @@ The Landsat vessel detection model detects ships in Landsat 8/9 scenes. We use L important for [Skylight](https://www.skylight.global/) (which is the primary use of this model within Ai2). -The model includes of a detector and a classifier: the detector detects ship-like objects, and the classifier refines these detections. The detector is trained on a dataset consisting of 7,954 Landsat patches (ranging from 384x384 to 768x768) with 18,509 ship labels. The classifier is trained on a dataset consisting of about 2,000 annotated detections (the input patch size is 64x64). See [our paper](https://arxiv.org/pdf/2312.03207) for more details about the model and dataset. +The model includes of a detector and a classifier: the detector detects ship-like objects, and the classifier refines these detections by pruning ones that it is confident are not ships. The detector is trained on a dataset consisting of 7,954 Landsat patches (ranging from 384x384 to 768x768) with 18,509 ship labels. The classifier is trained on a dataset consisting of 1,733 annotated detections, with each detection represented as a 64x64 patch centered at the position of a detected ship. See our paper for more details about the model and dataset.