Synonyme wurden verwendet für: Lernen Maschinelles Lernen
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1–20 von 104 Ergebnissen
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    A Combined Markov Chain and Reinforcement Learning Approach for Powertrain-Specific Driving Cycle Generation

    Dietrich, Maximilian / Sarkar, Mouktik / Chen, Xi | SAE Technical Papers | 2020
    Schlagwörter: Machine learning

    A Comparative Study of Longitudinal Vehicle Control Systems in Vehicle-to-Infrastructure Connected Corridor

    Fitzpatrick, Benjamin / King, Brian / Yoon, Hwan-Sik et al. | SAE Technical Papers | 2023
    Schlagwörter: Machine learning

    A Digital Twin Based Approach for Simulation and Emulation of an Automotive Paint Workshop

    Ruperez lng, Adrián / Martinez, Aitor / Lopez, Blanca et al. | SAE Technical Papers | 2021
    Schlagwörter: Machine learning

    A fuzzy system for automotive fault diagnosis: fast rule generation and self-tuning

    Yi Lu / Tie Qi Chen / Hamilton, B. | Tema Archiv | 2000
    Schlagwörter: maschinelles Lernen

    A Machine Learning-Based Design Representation Method for Designing Heterogeneous Microstructures

    Liu, Ruoqian | Online Contents | 2015
    Schlagwörter: Machine learning

    A Multiagency Long Short-Term Model Beamforming Prediction Model for Cellular Vehicle to Everything

    Liu, Sheng / Elangovan, Vivekanandh / Xiang, Weidong | SAE Technical Papers | 2023
    Schlagwörter: Machine learning

    Analysis and Interpretation of Data-Driven Closure Models for Large Eddy Simulation of Internal Combustion Engine

    Daly, Conor / Schmidt, David / Haghshenas, Majid et al. | SAE Technical Papers | 2021
    Schlagwörter: Machine learning

    An architectural framework for self-configuration and self-improvement at runtime

    Tomforde, Sven | Tema Archiv | 2011
    Schlagwörter: maschinelles Lernen

    An Auto-Encoder Based TinyML Approach for Real-Time Anomaly Detection

    Sai Charan, Kovuru | SAE Technical Papers | 2022
    Schlagwörter: Machine learning

    A New Optimal Design of Stable Feedback Control of Two-Wheel System Based on Reinforcement Learning

    Zhu, Xuebin / Yu, Zhenghong | SAE Technical Papers | 2023
    Schlagwörter: Machine learning

    A new scheme for vision based flying vehicle detection using motion flow vectors classification

    Taimori, Ali / Behrad, Alireza / Sabouri, Samira | Tema Archiv | 2009
    Schlagwörter: maschinelles Sehen , Lernen

    A Novel Approach to Light Detection and Ranging Sensor Placement for Autonomous Driving Vehicles Using Deep Deterministic Policy Gradient Algorithm

    Berens, Felix / Ambs, Jordan / Reischl, Markus et al. | SAE Technical Papers | 2024
    Schlagwörter: Machine learning

    Application of a Digital Twin Virtual Engineering Tool for Ground Vehicle Maintenance Forecasting

    Wagner, Adam / Eddy, Conner / Wagner, JOHN et al. | SAE Technical Papers | 2022
    Schlagwörter: Machine learning

    A Review and Outlook on Energy Consumption Estimation Models for Electric Vehicles

    Dubey, Abhishek / Laszka, Aron / Wu, Guoyuan et al. | SAE Technical Papers | 2021
    Schlagwörter: Machine learning

    Artificial Intelligence-Based Field-Programmable Gate Array Accelerator for Electric Vehicles Battery Management System

    Patil , B. P. / Nagarale, Satyashil D. | SAE Technical Papers | 2024
    Schlagwörter: Machine learning

    Artificial Intelligence for Damage Detection in Automotive Composite Parts: A Use Case

    Ciampaglia, Alberto / De Gregorio, Alessandro / Mastropietro, Antonio et al. | SAE Technical Papers | 2021
    Schlagwörter: Machine learning

    Artificial Intelligence in Aeronautical Systems: Statement of Concerns

    SAE Technical Papers | 2021
    Schlagwörter: Machine learning

    ATR applications of minimax entropy models of texture and shape

    Zhu, Song-Chun / Yuille, A.L. / Lanterman, A.D. | Tema Archiv | 2001
    Schlagwörter: Lernen , maschinelles Sehen

    Bridging the Gap between ISO 26262 and Machine Learning: A Survey of Techniques for Developing Confidence in Machine Learning Systems

    Joyce, Jeffrey / Serna, Jose / Millet, Laure et al. | SAE Technical Papers | 2020
    Schlagwörter: Machine learning