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Descripción

Intelligent Robotic Visual Perception with Deep Learning provides an in-depth exploration of deep learning-based robot Intelligent vision perception technologies that helps readers establish a solid foundation to learn about the applications and latest theoretical methods in visual perception. The book, in a comprehensive manner, covers the research aspects of deep learning technology in intelligent visual perception, ranging from methods to practical applications, algorithm analysis, and model construction. Users will find the latest international research trends that are essential for researchers working in the area.

  • Includes a detailed exploration of both algorithmic theory and practical applications
  • Provides a hands-on approach with case studies presented to help illustrate highly practical approaches
  • Shows readers how to construct intelligent robot vision perception systems tailored to real-world applications

1. Chapter 1 Introduction - p. 1 2. Chapter 2 Overview of the robot intelligent visual perception system - p. 11 3. Chapter 3 Overview of deep learning - p. 25 4. Chapter 4 Text detection and recognition in natural scenes - p. 61 5. Abstract - p. 61 6. 4.1 Overview - p. 61 7. 4.2 Scene text detection based on image segmentation - p. 69 8. 4.3 Sequence-based scene text recognition - p. 86 9. 4.4 A lightweight model-based inkjet text recognition system - p. 107 10. 4.4.5 Design and implementation of algorithm based on embedded system - p. 129 11. 4.4.6 System operational test - p. 135 12. 4.5 Chapter summary - p. 137 13. References - p. 137 14. Chapter 5 Visual object detection - p. 139 15. Chapter 6 Multiple object tracking - p. 191 16. Chapter 7 Image semantic segmentation - p. 237 17. Bibliography - p. 275 18. Index - p. 279

Descripcion
Descripción

Intelligent Robotic Visual Perception with Deep Learning provides an in-depth exploration of deep learning-based robot Intelligent vision perception technologies that helps readers establish a solid foundation to learn about the applications and latest theoretical methods in visual perception. The book, in a comprehensive manner, covers the research aspects of deep learning technology in intelligent visual perception, ranging from methods to practical applications, algorithm analysis, and model construction. Users will find the latest international research trends that are essential for researchers working in the area.

  • Includes a detailed exploration of both algorithmic theory and practical applications
  • Provides a hands-on approach with case studies presented to help illustrate highly practical approaches
  • Shows readers how to construct intelligent robot vision perception systems tailored to real-world applications

1. Chapter 1 Introduction - p. 1 2. Chapter 2 Overview of the robot intelligent visual perception system - p. 11 3. Chapter 3 Overview of deep learning - p. 25 4. Chapter 4 Text detection and recognition in natural scenes - p. 61 5. Abstract - p. 61 6. 4.1 Overview - p. 61 7. 4.2 Scene text detection based on image segmentation - p. 69 8. 4.3 Sequence-based scene text recognition - p. 86 9. 4.4 A lightweight model-based inkjet text recognition system - p. 107 10. 4.4.5 Design and implementation of algorithm based on embedded system - p. 129 11. 4.4.6 System operational test - p. 135 12. 4.5 Chapter summary - p. 137 13. References - p. 137 14. Chapter 5 Visual object detection - p. 139 15. Chapter 6 Multiple object tracking - p. 191 16. Chapter 7 Image semantic segmentation - p. 237 17. Bibliography - p. 275 18. Index - p. 279

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Autores
Muestra
Ficha Técnica