Deep Learning based Ship Detection in Satellite Imagery deep-learningship-detectionship-detection-dataset UpdatedAug 21, 2024 Jupyter Notebook Sup3Legacy/TIPE Star0 TIPE MPSI/MP* 2018-2020 image-processingdatasetartificial-neural-networksimage-generationdiamond-square-algorithmperlin-noiseheightmapconvolutional...
Satellite imagery datasets containing ships. A list of radar and optical satellite datasets for ship detection, classification, semantic segmentation and instance segmentation tasks. 📡 Radar Satellite Datasets A) Table with available datasets: B) Information about the datasets: 1. SSDD (SAR Ship De...
Previous work has largely relied on the identification of ship tracks by eye from near-infrared satellite imagery (for example, 2.1 or 3.7 µm channels) and the logging of their positions by hand15,22,23. Here, we use datasets of ship emissions, which are advected with the wind usin...
Franklin, S.E., Giles, P.T.: Radiometric processing of aerial and satellite remote-sensing imagery. Comput. Geosci. 21(3), 413–423 (1995) Article Google Scholar Giuffrida, G., et al.: CloudScout: a deep neural network for on-board cloud detection on hyperspectral images. Remote Sens...
deep-learning yolo ship object-detection satellite-imagery darknet Updated Dec 2, 2020 Python nasir6 / py_cfar Star 66 Code Issues Pull requests Vessel Detection in Synthetic Aperture Radar(SAR) Images ship sar vessel synthetic-aperture-radar vessel-detection dete cfar ca-cfar python-cfar ...
To accurately detect ships of arbitrary orientation in optical remote sensing images, we propose a two-stage CNN-based ship-detection method based on the ship center and orientation prediction. Center region prediction network and ship orientation classi
The SSDD is specifically designed for ship detection in satellite imagery, comprising 1160 high-resolution remote sensing images. It is divided into training, validation, and test sets in an 8:1:1 ratio, containing a single category: ship. The HRSC2016 dataset focuses on ship target detection ...
Ship detection from synthetic aperture radar (SAR) imagery is crucial for various fields in real-world applications. Numerous deep learning-based detectors have been investigated for SAR ship detection, which requires a substantial amount of labeled data
You Only Look Twice: Rapid Multi-Scale Object Detection In Satellite Imagery. arXiv 2018, arXiv:1805.09512. [Google Scholar] Li, Q.; Mou, L.; Liu, Q.; Wang, Y.; Zhu, X.X. HSF-Net: Multiscale Deep Feature Embedding for Ship Detection in Optical Remote Sensing Imagery. IEEE Trans....
predict_pv_yield - Use machine learning to map satellite imagery of clouds to solar PV yield. solar-panel-detection - Using a combination of AI (machine vision), open data and short-term forecasting, the project aims to determine the amount of solar electricity being put into the UK grid ...