Titlebook: Geospatial Intelligence; Applications and Fut Fatimazahra Barramou,El Hassan El Brirchi,Youness Book 2022 The Editor(s) (if applicable) an

Ancillary

Lithological Mapping for a Semi-arid Area Using GEOBIA and PBIA Machine Learning Approaches with Sent can automatically and promptly identify lithological units over large areas. Most available Pixel-Object Based comparative classification studies have been applied to land use land cover (LULC) studies; however, this research aims to evaluate and compare the performance of these digital classifica

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Optimization of Object-Based Image Analysis with Genetic Programming to Generate Explicit Knowledge ms, especially the evolutionary process, can extract useful knowledge that can be used in different fields. In this paper, object-oriented classification was used, more particularly, the object-based image analysis approach (OBIA) is used to classify a large feature space composed of a very high spa

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nautical

Motilin

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Peripheral Artery Vascular Emergency,nts and Natural Language Processing (NLP) tools. This approach has been applied to flood forecasting to mitigate future risks and flood damage since the dynamics of real-world events such as floods prompt users to discuss the topic. The approach is based on the appropriate filtering and preprocessin

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https://doi.org/10.1007/978-3-642-80381-9, but they turn out to be a complex task due to the complexity of the objects. This paper discusses issues related to the detection and segmentation of roads in very high-resolution aerial images. In order to resolve these issues, we propose in this paper the use, deployment, and validation of deep

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L. W. Storz,D. Lorenz,J. Winterganizations (such as the Euro control and International Civil Aviation Organization—ICAO) following their departure trajectories (the standard instrument departures—SIDs or omnidirectional trajectories), answering to the order of aircrafts’ demands of taxiing and taking off, especially when followin

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H. Schumacher,N. Diehm,J. R. AllenbergDoS) cyber-attacks targeting the networks of drones. The proposed model is autonomous, characterized by its high performance and enables the detection of known and unknown DoS attacks in UAV networks with high accuracy and low false-positives and false-negatives rates. This approach is intended to a

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