Titlebook: Intelligent Data Engineering and Automated Learning – IDEAL 2022; 23rd International C Hujun Yin,David Camacho,Peter Tino Conference procee

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Detection of False Information in Spanish Using Machine Learning Techniquestypes of false information and claims such as articles, posts on Facebook, WhatsApp’s messages, tweets, and others. The results evidence how usage of machine learning techniques can help in the identification of false statements with more than 88% accuracy, and in collecting samples of false informa

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Federating Unlabeled Samples: A Semi-supervised Collaborative Framework for?Whole Slide Image Analysotes multi-institutional training of deep learning models while integrating unlabeled collaborating data sources into the federated setup. The experimental results show a better performance for models trained under a federated setting with both labeled and unlabeled data. Optimally, this framework w

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Explanations of?Performance Differences in?Segment Lining for?Tunnel Boring Machinesediction and derive regions of interest in ring-building sequences leading to specific performance classifications. Finally, we discuss how the observations from our study can contribute to designing assistance systems that support operators toward a more efficient ring-building process.

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Endowing Intelligent Vehicles with?the?Ability to?Learn User’s Habits and?Preferences with?Machine Lseat poses. The developed models were trained, evaluated, and validated with different datasets in the Portuguese city of Braga. The results prove that the vehicle efficiently learns the routines of several users with varying complexities. Prediction errors happen in cases of an exceptional, one-tim

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Asifuzzaman Lasker,Mridul Ghosh,Sk Md Obaidullah,Chandan Chakraborty,Teresa Goncalves,Kaushik Royrden. So sind wir dankbar, dass Anna Daun hierin und in die Erfassung, überarbeitung und Fertigstellung des Manuskripts viel Zeit investierte. Unt- stützt wurde sie am Ende von Katharina Holzfu?, der wir an dieser Stelle he- lich danken. K978-3-531-15462-6978-3-531-90568-6

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