<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Satellite Imagery on DeepLearning.Earth</title><link>https://deeplearning.earth/tags/satellite-imagery/</link><description>Recent content in Satellite Imagery on DeepLearning.Earth</description><generator>Hugo -- gohugo.io</generator><language>en-us</language><lastBuildDate>Wed, 08 Feb 2023 15:11:48 +0000</lastBuildDate><atom:link href="https://deeplearning.earth/tags/satellite-imagery/index.xml" rel="self" type="application/rss+xml"/><item><title>Is YOLOv8 suitable for satellite imagery?</title><link>https://deeplearning.earth/posts/2023-02-08_is_yolo8_suitable_for_satellite_imagery/</link><pubDate>Wed, 08 Feb 2023 15:11:48 +0000</pubDate><guid>https://deeplearning.earth/posts/2023-02-08_is_yolo8_suitable_for_satellite_imagery/</guid><description>The latest YOLO version has been published Link to heading YOLOv8 is the latest version of the YOLO object detection and image segmentation models developed by Ultralytics. YOLOv8 is a cutting-edge, state-of-the-art (SOTA) model that builds upon the success of previous YOLO versions and introduces new features and improvements to further boost performance and flexibility.
Performances of the YOLO series (source)
YOLOv8 is designed to be fast, accurate and user-friendly, making it a popular choice among researchers and practitioners in computer vision and AI.</description></item></channel></rss>