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    Zusammenfassung, kritische Würdigung und Ausblick

    Broch, Florian | Springer Verlag | 2017
    Keywords: Data Mining and Knowledge Discovery

    WSN-Based Driver Cabinet Monitoring System for the Fleet of Long-Route Vehicles

    Dubey, Jyoti R. / Bhavsar, Ankit R. | Springer Verlag | 2020
    Keywords: Data Mining and Knowledge Discovery

    Wearable Technology Adaptation to Aviation Cabin Crew’s Fatigue Assessments

    Çevik, İrem / Dahanayake, Ajantha | Springer Verlag | 2021
    Keywords: Data Mining and Knowledge Discovery

    Wavelet Packet Energy Entropy Based Feature Analysis of Seismic Signals from Vehicle Targets

    Ding, Kai / Li, Xinghua / Li, Hao et al. | Springer Verlag | 2020
    Keywords: Data Mining and Knowledge Discovery

    Visualization Tools for Traffic Congestion Estimation

    Petrovska, Natasha / Stevanovic, Aleksandar / Furht, Borko | Springer Verlag | 2016
    Keywords: Data Mining and Knowledge Discovery

    Visual Analysis for Civil Aviation Passenger Reservation Data Characteristics Based on Uncertainty Measurement

    He, Huaiqing / Du, Hongrui / Liu, Haohan | Springer Verlag | 2016
    Keywords: Data Mining and Knowledge Discovery

    Vision-Based Irregular Car Parking Behaviors Detection in the Underground Garage

    Wang, Pengfei / Xu, Zhenyuan / Cen, Libin et al. | Springer Verlag | 2020
    Keywords: Data Mining and Knowledge Discovery

    Vision-Based Driver Authentication and Alertness Detection Using HOG Feature Descriptor

    Nissimagoudar, P. C. / Nandi, A. V. / Gireesha, H. M. et al. | Springer Verlag | 2020
    Keywords: Data Mining and Knowledge Discovery

    Verifizierung des Konzepts anhand einer Fallstudie

    Broch, Florian | Springer Verlag | 2017
    Keywords: Data Mining and Knowledge Discovery

    Vehicle-Road Multi-View Interactive Data Fusion

    Zhang, Xinyu / Li, Jun / Li, Zhiwei et al. | Springer Verlag | 2023
    Keywords: Data Mining and Knowledge Discovery

    V2V-DDS Approach to Provide Sheltered Communication Over ALTERATION ATTACK to Control Against Vehicular Traffic

    Prittopaul, P. / Usha, M. / Santhosh, M. V. S. et al. | Springer Verlag | 2017
    Keywords: Data Mining and Knowledge Discovery

    Urban Traffic Monitoring from Mobility Data

    Liu, Zhidan / Wu, Kaishun | Springer Verlag | 2021
    Keywords: Data Mining and Knowledge Discovery

    Urban Traffic Management Utilizing Soft Measures: A Case Study of Volos City

    Karatsoli, Maria / Karakikes, Ioannis / Nathanail, Eftihia | Springer Verlag | 2018
    Keywords: Data Mining and Knowledge Discovery

    Understanding Taxi Travel Demand Patterns Through Floating Car Data

    Nuzzolo, Agostino / Comi, Antonio / Papa, Enrica et al. | Springer Verlag | 2018
    Keywords: Data Mining and Knowledge Discovery

    Traffic Noise Reduction and Sustainable Transportation: A Case Survey in the Cities of Athens and Thessaloniki, Greece

    Profillidis, Vassilios / Botzoris, George / Galanis, Athanasios | Springer Verlag | 2018
    Keywords: Data Mining and Knowledge Discovery

    Traffic Control and Management Over IoT for Clearance of Emergency Vehicle in Smart Cities

    Rajak, Biru / Kushwaha, Dharmender Singh | Springer Verlag | 2018
    Keywords: Data Mining and Knowledge Discovery

    Traffic Congestion Visualization by Traffic Parameters in India

    Tsuboi, Tsutomu | Springer Verlag | 2019
    Keywords: Data Mining and Knowledge Discovery

    Traffic Big Data and Its Application in Road Traffic Performance Evaluation: Illustrated by the Case of Shenzhen

    Qiu, Jiandong / Chen, Wei | Springer Verlag | 2017
    Keywords: Data Mining and Knowledge Discovery

    Traffic and Environmental Rehabilitation of the Agioi Anargyroi Square of the Municipality of Agioi Anargyroi – Kamatero

    Margariti, Christina / Zervas, Efthimios / Nalmpantis, Dimitrios | Springer Verlag | 2018
    Keywords: Data Mining and Knowledge Discovery

    Theoretical Foundations

    Mohammad, Yasser / Nishida, Toyoaki | Springer Verlag | 2015
    Keywords: Data Mining and Knowledge Discovery

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