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Titlebook: Space Fostering African Societies; Developing the Afric Annette Froehlich Book 2021 The Editor(s) (if applicable) and The Author(s), under

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,Egypt’s Remote Sensing Land Use Classification Using Deep Learning,assifier layers of the pre-trained CNN networks AlexNet, VGG16 and ResNet. In general the SVM classifier outperforms the other two tested classifiers (KNN and the Naïve Bayes). The highest accuracy, 94.7%, achieved by ResNet model on the RS19 dataset. We obtained our dataset from Google Earth Engine
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Democratising the Signal: A Conceptual Beneficiation Model of Space Technology for Lesser Privilege in existence? The purpose of this work was to propose a simple model to identify additional application opportunities for existing SDG supporting space applications, especially for the benefit of people in infrastructure-challenged areas such as Sub-Saharan Africa. The scope of the work was limited
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On the Feasibility of Landing the Dream Chaser Space Vehicle in South Africa,entry and landing of spacecraft in South Africa. Elements addressed in this investigation range from physical facilities such as the airports, workshops and laboratories, through Dream Chaser specific requirements and specifications, right down to space and civil aviation regulations. Relevant infor
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