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Concept Drift Detection and Adaptation for Robotics and Mobile Devices in Federated and Continual Settings., , , , and . WAF, volume 1285 of Advances in Intelligent Systems and Computing, page 79-93. Springer, (2020)Inertial Navigation with Mobile Devices: A Robust Step Count Model., , , and . ROBOT (1), volume 693 of Advances in Intelligent Systems and Computing, page 666-678. Springer, (2017)Automatic Selection of User Samples for a Non-collaborative Face Verification System., , , , and . ROBOT (1), volume 693 of Advances in Intelligent Systems and Computing, page 555-566. Springer, (2017)Concept drift detection and adaptation for federated and continual learning., , , , , and . CoRR, (2021)Federated Learning from Demonstration for Active Assistance to Smart Wheelchair Users., and . IROS, page 9326-9331. IEEE, (2022)Learning from the Individuals and the Crowd in Robotics and Mobile Devices., , , , and . ROBOT (2), volume 1093 of Advances in Intelligent Systems and Computing, page 632-643. Springer, (2019)Robust Heading Estimation in Mobile Phones., , , , and . IWINAC (2), volume 11487 of Lecture Notes in Computer Science, page 180-190. Springer, (2019)Artificial intelligence within the interplay between natural and artificial computation: Advances in data science, trends and applications., , , , , , , , , and 9 other author(s). Neurocomputing, (2020)Non-IID data and Continual Learning processes in Federated Learning: A long road ahead., , , , and . Inf. Fusion, (2022)Ensemble and continual federated learning for classification tasks., , , , and . Mach. Learn., 112 (9): 3413-3453 (September 2023)