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Uncertainty Analysis of Deep Neural Network for Classification of Vulnerable Road Users using micro-Doppler.

, , , , and . WiSNet, page 23-26. IEEE, (2020)

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XAI-BayesHAR: A novel Framework for Human Activity Recognition with Integrated Uncertainty and Shapely Values., , , and . ICMLA, page 1281-1288. IEEE, (2022)Bayesian Architecture and Learning Algorithms for Recognition of Vulnerable Road Users using Automotive Radar.. University of Erlangen-Nuremberg, Germany, (2022)Validation and Analysis of the Propagation Channel at 60 GHz for Vehicular Communication., , , , , , and . VTC Fall, page 1-7. IEEE, (2021)Programmable Systems for Intelligence in Automobiles (PRYSTINE): Technical Progress after Year 2., , , , , , , , , and 21 other author(s). DSD, page 360-369. IEEE, (2020)Bayesradar : Bayesian Metric-Kalman Filter Learning for Improved and Reliable Radar Target Classification., , , , , and . MLSP, page 1-6. IEEE, (2021)XAI-Increment: A Novel Approach Leveraging LIME Explanations for Improved Incremental Learning., , , , and . CoRR, (2022)Integrated Classification and Localization of Targets Using Bayesian Framework In Automotive Radars., , , , , and . ICASSP, page 4060-4064. IEEE, (2021)A Bayesian Framework for Integrated Deep Metric Learning and Tracking of Vulnerable Road Users Using Automotive Radars., , , , , and . IEEE Access, (2021)Channel Characterization at 77 GHz for Vehicular Communication., , , , , and . VNC, page 1-4. IEEE, (2020)Full Physical Layer Simulation Tool to Design Future 77 GHz JCRS-Applications., , , , , , and . IEEE Access, (2022)