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    PSO-based Machine Learning Methods for Predicting Ground Surface Displacement Induced by Shallow Underground Excavation Method

    Kong, Fanchao / Tian, Tao / Lu, Dechun et al. | Springer Verlag | 2023
    Schlagwörter: Machine learning methods

    Traffic Sign Detection and Recognition

    Pillai, Preeti S. / Kinnal, Bhagyashree / Pattanashetty, Vishal et al. | Springer Verlag | 2022
    Schlagwörter: Machine learning

    Architecture and Implementation of a Scalable Sensor Data Storage and Analysis System Using Cloud Computing and Big Data Technologies

    Aydin, Galip / Hallac, Ibrahim Riza / Karakus, Betul et al. | Tema Archiv | 2015
    Schlagwörter: maschinelles Lernen

    Sampling-based exploration strategies for mobile robot autonomy

    Freier Zugriff
    Steinbrink, Marco | TIBKAT | 2023
    Schlagwörter: Maschinelles Lernen

    Artificial Intelligence

    Guo, Zhiwei / Yu, Keping | Springer Verlag | 2021
    Schlagwörter: Machine learning , Machine learning AI , Supervised learning , Unsupervised learning , Semi-supervised learning , Reinforcement learning , Deep learning AI

    Machine Learning Applications for Internet of Flying Vehicles in Case of Critical and Environmental Cases

    Dimililer, Kamil / Ever, Yoney Kirsal / Al-Turjman, Fadi | Springer Verlag | 2020
    Schlagwörter: Machine learning

    Characterizing Smart Grid Events Using Clustering Methods

    Klinginsmith, Eric / Barella, Richard / Zhao, Xinghui et al. | Springer Verlag | 2017
    Schlagwörter: Machine learning

    Intelligence After Next: Breaking Past AI's Confirmation Bias

    M. Shea | NTIS | 2021
    Schlagwörter: Machine learning

    3D vehicle sensor based on monocular vision

    Ponsa, D. / Lopez, A. / Lumbreras, F. et al. | Tema Archiv | 2005
    Schlagwörter: maschinelles Sehen , Lernen

    Artificial Intelligence: Need, Evolution, and Applications for Transportation Systems

    Dai, Yueyue / Ma, Huihui | Springer Verlag | 2021
    Schlagwörter: Machine learning , Reinforcement learning , Supervised learning , Semi-supervised learning , Meta-learning , Unsupervised learning , Federated learning , Transfer learning

    Developing an Air Force Retention Early Warning System: Concept and Initial Prototype

    D. Schulker / L. M. Harrington / M. Walsh et al. | NTIS | 2021
    Schlagwörter: Machine learning

    Pioneering Data Quality and Security in Smart Grid

    Roy, Bright / Tripathi, Prashant / Goel, Rahul | Springer Verlag | 2022
    Schlagwörter: Machine learning

    Stereo vision system for longitudinal and lateral control of heterogeneous vehicle platoons on unstructured environment

    Alfraheed, Mohammad | Tema Archiv | 2012
    Schlagwörter: maschinelles Lernen , maschinelles Sehen

    Deep Learning Mechanism for Region Based Urban Traffic Flow Forecasting

    Bansal, Nishu / Bali, Rasmeet Singh | Springer Verlag | 2023
    Schlagwörter: Machine Learning

    Traffic sign recognition using evolutionary Adaboost detection and forest-ECOC classification

    Baro, X. / Escalera, S. / Vitria, J. et al. | Tema Archiv | 2009
    Schlagwörter: maschinelles Sehen , Lernen

    Acoustic sleepiness analysis - using speech input from driver assistance systems for the phonetic detection of critical driver states

    Krajewski, J. / Sommer, D. / Schupp, T. et al. | Tema Archiv | 2009
    Schlagwörter: maschinelles Lernen

    Traffic Light Control and Machine Learning: A Systematic Mapping Review

    Borges, Dimitrius F. / Moreira, Edmilson M. / de Souza, Adler D. et al. | Springer Verlag | 2021
    Schlagwörter: Machine learning , Reinforcement learning

    Lane change intent analysis using robust operators and sparse Bayesian learning

    McCall, J.C. / Wipf, D.P. / Trivedi, M.M. et al. | Tema Archiv | 2007
    Schlagwörter: maschinelles Sehen , Lernen

    Deep Learning-Based Detection of Catenary Support Component Defect and Fault in High-Speed Railways

    Liu, Zhigang / Liu, Wenqiang / Zhong, Junping | TIBKAT | 2023
    Schlagwörter: Machine learning , Maschinelles Lernen

    Image processing system for pedestrian monitoring using neural classification of normal motion patterns

    Boghossian, B.A. / Velastin, S.A. | Tema Archiv | 1999
    Schlagwörter: maschinelles Sehen , Lernen

    Obstacle avoidance learning for a wheeled lunar rover based on its local relative pose

    Pan, Haining / Lei, Zhenwu / Cui, Pingyuan et al. | Tema Archiv | 2009
    Schlagwörter: Lernen , maschinelles Sehen

    Exploring Image-Based Classification to Detect Vehicle Make and Model. Final Report

    J. B. Flora / M. Alam / A. H. Yousef et al. | NTIS | 2013
    Schlagwörter: Machine learning

    Deep Neural Network-Based Prediction of High-Speed Train-Induced Subway Track Vibration

    Wieczorek, Michał / Siłka, Jakub / Woźniak, Marcin | Springer Verlag | 2021
    Schlagwörter: Deep learning , Machine learning

    Neurons that know how to drive

    Rosenblum, M. | Tema Archiv | 2000
    Schlagwörter: maschinelles Sehen , Lernen

    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

    Study of Automatic Anomalous Behaviour Detection Techniques for Maritime Vessels

    Abdoulaye Sidibé | Online Contents | 2017
    Schlagwörter: Active learning , Learning behaviour , Machine learning

    Combat vehicle classification using machine learning

    Zeng, H. / Huang, J. / Liang, Y. | Tema Archiv | 1999
    Schlagwörter: maschinelles Lernen , Lernen am Beispiel

    Future Autonomous Transportation: Challenges and Prospective Dimensions

    Akhtar, Muhammad Waseem / Hassan, Syed Ali | Springer Verlag | 2021
    Schlagwörter: Machine learning

    The Future of Car Automation Field with Smart Driverless Technologies

    Thombare, Shreyas Shivajirao | Springer Verlag | 2022
    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

    Robust servo-control for underwater robots using banks of visual filters

    Sattar, J. / Dudek, G. | Tema Archiv | 2009
    Schlagwörter: Lernen , maschinelles Sehen

    Critical motion detection of nearby moving vehicles in a vision-based driver-assistance system

    Cherng, Shen / Fang, Chiung-Yao / Chen, Chia-Pei et al. | Tema Archiv | 2009
    Schlagwörter: maschinelles Sehen , Lernen

    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

    Dialogue Patterns and Misunderstandings

    J. Aberdeen / L. Ferro | NTIS | 2003
    Schlagwörter: Machine learning , Learning

    Automatic Geographic Enrichment by Multi-modal Bike Sensing

    Verstockt, Steven / Slavkovikj, Viktor / Potter, Pieterjan De et al. | Tema Archiv | 2014
    Schlagwörter: maschinelles Lernen

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

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

    Clustering sensor data for autonomous terrain identification using time-dependency

    Giguere, Philippe / Dudek, Gregory | Tema Archiv | 2009
    Schlagwörter: maschinelles Lernen

    Optical flow-based obstacle detection and avoidance behaviors for mobile robots used in unmanned planetary exploration

    Dur, E. | Tema Archiv | 2009
    Schlagwörter: Lernen , maschinelles Sehen

    Visual recognition of hexagonal headed bolts by comparing ICA to wavelets

    Mazzeo, P.L. / Ancona, N. / Stella, E. et al. | Tema Archiv | 2003
    Schlagwörter: maschinelles Sehen , Lernen

    Pattern recognition for nondestructive evaluation

    Amirfathi, M.M. / Morris, S. / O'Rorke, P. et al. | Tema Archiv | 1991
    Schlagwörter: SYMBOLIC MACHINE LEARNING ALGORITHM

    Adaptive navigation of automated vehicles by image analysis techniques

    Tsai, W. / Chen, Y. | Tema Archiv | 1986
    Schlagwörter: MASCHINELLES SEHEN , PATH NETWORK LEARNING

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