Titlebook: Geo-Environmental Hazards using AI-enabled Geospatial Techniques and Earth Observation Systems; Tanupriya Choudhury,Bappaditya Koley,Atul

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Visual Media Super-Resolution Using Super-Resolution Generative Adversarial Networks,cessing and video super-resolution. Recovery of a high-resolution (HR) picture from a low-resolution (LR) counterpart is the aim of super-resolution (SR). It is an enduring and difficult part of image processing with numerous real-world applications including reconstruction of medical images, face r

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https://doi.org/10.1007/978-3-642-91407-2combination of both supervised and unsupervised algorithms. Reinforcement learning will be the most useful one in case of real environments like playing games, driving a car and playing a piano. In this case, a machine will learn on its own by getting the rewards and penalties. Additionally, ensembl

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https://doi.org/10.1007/978-3-642-94305-8 by utilizing optical and digital elevation satellite images, field observations, secondary data, GIS, and remote sensing tools. By adopting analytical hierarchy process (AHP) calculation methods, the weights of the selected thematic layers and their respective subthemes have been computed. After ca

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https://doi.org/10.1007/978-3-663-04622-6ere considered to be training samples and the remaining 30% to be testing samples. Feature importance was computed with the game theory-based SHapley Additive exPlanations (SHAP) approach. Evaluation of fulfillment of the proposed methods was accomplished with area under the receiver operating chara

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