• Medientyp: Buch
  • Titel: Roadside video data analysis : deep learning
  • Beteiligte: Verma, Brijesh [VerfasserIn]; Zhang, Ligang [VerfasserIn]; Stockwell, David [VerfasserIn]
  • Erschienen: Singapore: Springer, [2017]
  • Erschienen in: Studies in computational intelligence ; 711
  • Umfang: xxv, 189 Seiten; Illustrationen, Diagramme; 25 cm
  • Sprache: Englisch
  • ISBN: 9789811045387
  • RVK-Notation: ST 620 : Technik
    ZO 4620 : Verkehrsleitsysteme, Telematik im Straßenverkehr
    ST 300 : Allgemeines
  • Schlagwörter: Datenanalyse > Deep learning
    Verkehrsbegleitgrün > Straßenrand > Video > Datenanalyse
  • Entstehung:
  • Anmerkungen: Literaturangaben
  • Beschreibung: This book highlights the methods and applications for roadside video data analysis, with a particular focus on the use of deep learning to solve roadside video data segmentation and classification problems. It describes system architectures and methodologies that are specifically built upon learning concepts for roadside video data processing, and offers a detailed analysis of the segmentation, feature extraction and classification processes. Lastly, it demonstrates the applications of roadside video data analysis including scene labelling, roadside vegetation classification and vegetation biomass estimation in fire risk assessment

    Chapter 1: Introduction -- Chapter 2: Roadside Video Data Analysis Framework -- Chapter 3: Non-Deep Learning Techniques for Roadside Video Data Analysis -- Chapter 4: Deep Learning Techniques for Roadside Video Data Analysis -- Chapter 5: Case Study: Roadside Video Data Analysis for Fire Risk Assessment -- Chapter 6: Conclusion and Future Insight - References
  • Weitere Bestandsnachweise
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