Titlebook: Soil Dynamics and Soil-Structure Interaction for Resilient Infrastructure; Proceedings of the 1 Tarek Abdoun,Sherif Elfass Conference proce

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Soil Dynamics and Soil-Structure Interaction for Resilient Infrastructure978-3-319-63543-9Series ISSN 2366-3405 Series E-ISSN 2366-3413

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Tarek Abdoun,Sherif ElfassIncludes twenty peer-reviewed papers, submitted by renowned international researchers.Covers wide range of topics in soil-structure-interaction and soil dynamics.Discusses case studies as well as phys

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layers, which results in an effective combination of low-level and high-level features and efficient information flow throughout the network. To train and evaluate our network, we use a dataset of 181 high-resolution CLE images. Both quantitative and qualitative results indicate superiority of the

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Ahmed Mohamed,Marawan Shahin,Herbert Klapperichn of PK parameters. Experiments on clinical brain DCE datasets demonstrate the efficacy of our approach in terms of fidelity of PK parameter reconstruction and significantly faster parameter inference compared to a model-based iterative reconstruction method.

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Sidi Mohammed El-Amine Bourdim,Lokmane El-Hakim Chekroun,Abdelkader Benanane,Abdelillah Bourdimtations at both a feature-level and prediction-level to predict image quality grades. Experiments on our EyeQ dataset show that our MCF-Net obtains a state-of-the-art performance, outperforming the other deep learning methods. Furthermore, we also evaluate diabetic retinopathy (DR) detection methods

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Binu Sharma,Noorjahan Begum (DAP) to improve the accuracy of liver segmentation in CT images. We trained the semi-supervised adversarial learning model using both annotated and unannotated images. The DAP, which is based on the probability atlas of organ (liver) and contains prior information such as the shape and position, i