Conference paper Open Access

Automatic Maritime Object Detection Using Satellite imagery

Konstantina Bereta; Raffaele Grasso; Dimitris Zissis

In this paper we present an approach for performing object classification and segmentation in satellite images for the Maritime domain. 
We employ neural network architectures for object classification and segmentation tasks in order to identify different classes of objects in satellite imagery for the maritime domain, such as vessels, land (e.g., port terminals), clouds, etc. We compare the accuracy of different neural network architectures and present the results of our experimental evaluation.

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Publication date:
October 9, 2020
DOI:
10.5281/zenodo.4074827

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10.5281/zenodo.4074827

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Grants:
European Commission:
  • INFORE - Interactive Extreme-Scale Analytics and Forecasting (825070)
Meeting:
IEEE Oceans 2020, October 5-14, 2020
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License (for files):
Creative Commons Attribution 4.0 International

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