Roadside Video Data Analysis Deep Learning /

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...

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Detaylı Bibliyografya
Asıl Yazarlar: Verma, Brijesh (Yazar), Zhang, Ligang (Yazar), Stockwell, David (Yazar)
Müşterek Yazar: SpringerLink (Online service)
Materyal Türü: e-Kitap
Dil:İngilizce
Baskı/Yayın Bilgisi: Singapore : Springer Nature Singapore : Imprint: Springer, 2017.
Edisyon:1st ed. 2017.
Seri Bilgileri:Studies in Computational Intelligence, 711
Konular:
Signal processing.
Computational intelligence.
User interfaces (Computer systems).
Human-computer interaction.
Image processing > Digital techniques.
Computer vision.
Transportation engineering.
Traffic engineering.
Signal, Speech and Image Processing.
Computational Intelligence.
User Interfaces and Human Computer Interaction.
Computer Imaging, Vision, Pattern Recognition and Graphics.
Transportation Technology and Traffic Engineering.
Online Erişim:Full-text access
OPAC'ta görüntüle
İçindekiler:
  • 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.

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