https://deeplearning.earth/tags/yolo/Recent content in Yolo on DeepLearning.EarthHugo -- gohugo.ioen-usWed, 08 Feb 2023 15:11:48 +0000https://deeplearning.earth/posts/2023-02-08_is_yolo8_suitable_for_satellite_imagery/Wed, 08 Feb 2023 15:11:48 +0000https://deeplearning.earth/posts/2023-02-08_is_yolo8_suitable_for_satellite_imagery/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.https://deeplearning.earth/posts/2022-06-15_oil-storage-detection-on-airbus-imagery-with-yolox/Wed, 15 Jun 2022 19:17:31 +0000https://deeplearning.earth/posts/2022-06-15_oil-storage-detection-on-airbus-imagery-with-yolox/Introduction Link to heading Last year, Airbus Intelligence published a few Machine Learning Datasets on the Kaggle platform. These datasets are samples from much larger and more comprehensive datasets provided by Airbus. Nevertheless, they are good datasets to start with and build upon if you wish to learn more about Earth Observation imagery and Deep Learning. In this article, we will analyse the Airbus Oil Storage dataset. It contains one hundred SPOT images and a little over 13,500 annotated POL (Petroleum, Oil and Lubricant) storage.https://deeplearning.earth/posts/2021-09-16_detecting-aircraft-on-airbus-pleiades-imagery-with-yolov5/Thu, 16 Sep 2021 15:11:48 +0000https://deeplearning.earth/posts/2021-09-16_detecting-aircraft-on-airbus-pleiades-imagery-with-yolov5/Introduction Link to heading Recently Airbus Intelligence has published a few Machine Learning Datasets on the Kaggle platform. These datasets are samples from much larger and more comprehensive datasets provided by Airbus. Nevertheless, they are good datasets to start with and build upon if you wish to learn more about Earth Observation imagery and Deep Learning. In this article, we will analyse the Airbus aircraft dataset. It contains one hundred civilian airports and a little over 3,000 annotated commercial aircrafts.