Roadside video data analysis : deep learning
Verma, Brijesh,
Roadside video data analysis : deep learning Brijesh Verma, Ligang Zhang, David Stockwell. - 1 recurso en línea (xxv, 189 páginas) ilustraciones (algunas a color) - Studies in computational intelligence volume 711 1860-949X .
SpringerLink
Incluye referencias bibliográficas
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.
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.
9789811045394 9811045399
Aprendizaje automático
Q325.5 / V476 2017 EB
Roadside video data analysis : deep learning Brijesh Verma, Ligang Zhang, David Stockwell. - 1 recurso en línea (xxv, 189 páginas) ilustraciones (algunas a color) - Studies in computational intelligence volume 711 1860-949X .
SpringerLink
Incluye referencias bibliográficas
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.
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.
9789811045394 9811045399
Aprendizaje automático
Q325.5 / V476 2017 EB