Titlebook: Artificial Intelligence Applications and Innovations; 20th IFIP WG 12.5 In Ilias Maglogiannis,Lazaros Iliadis,Antonios Papale Conference pr

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https://doi.org/10.1007/978-3-662-64165-1Long Short-Term Memory to determine which machine learning model offers the most robust predictions, enabling more effective and sustainable groundwater management. We observe that the XGBoost model outperforms its counterparts in terms of predictive accuracy. The findings of this study offer critic

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Shoulder Instability in Handball Playerses results comparable to state-of-the-art approaches of similar depth and parameter count. Moreover, in larger image dimensions, using FFCs instead of self-attention allows for batch sizes up to twice as large and iterations up to 26% faster.

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Markus Wurm M.D.,Lior Laver M.D.oped model can forecast longitudinal acceleration 0.1?s ahead by utilizing the preceding 0.1?s of sensor data with high accuracy. Comparing our results with those published in the literature, we can conclude that the model we developed provides significantly more accurate predictions for longitudina

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