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WhONet: Wheel Odometry Neural Network for Vehicular Localisation in GNSS-Deprived Environments., , , , , and . CoRR, (2021)Probabilistic Analysis of Abnormal Behaviour Detection in Activities of Daily Living., , , , , , and . PerCom Workshops, page 461-466. IEEE, (2019)Visualization of the significance of Receiver Operating Characteristics based on confidence ellipses., and . Comput. Phys. Commun., 185 (3): 1172-1176 (2014)Learning Driver Braking Behavior Using Smartphones, Neural Networks and the Sliding Correlation Coefficient: Road Anomaly Case Study., , and . IEEE Trans. Intell. Transp. Syst., 20 (1): 65-74 (2019)VISROC 2.0: Updated Software for the Visualization of the significance of Receiver Operating Characteristics based on confidence ellipses., , , and . Comput. Phys. Commun., (2022)An Application of the Coherent Noise Model for the Prediction of Aftershock Magnitude Time Series., and . Complex., (2017)Learning Uncertainties in Wheel Odometry for Vehicular Localisation in GNSS Deprived Environments., , , and . ICMLA, page 741-746. IEEE, (2020)A Quaternion Gated Recurrent Unit Neural Network for Sensor Fusion., , , and . Inf., 12 (3): 117 (2021)Detecting anomalies in time series data via a deep learning algorithm combining wavelets, neural networks and Hilbert transform., , , and . Expert Syst. Appl., (2017)Natural Time Analysis: The Area under the Receiver Operating Characteristic Curve of the Order Parameter Fluctuations Minima Preceding Major Earthquakes., , , and . Entropy, 22 (5): 583 (2020)