For Facial Recognition, Object Detection, and Pattern Recognition Using Python
Buch, Englisch, 169 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 295 g
ISBN: 978-1-4842-4148-6
Verlag: Apress
The next section looks at advanced machine learning and deep learning methods for image processing and classification. You’ll work with concepts such as pulse coupled neural networks, AdaBoost, XG boost, and convolutional neural networks for image-specific applications. Later you’ll explore how models are made in real time and then deployed using various DevOps tools.
All the conceptsin Practical Machine Learning and Image Processing are explained using real-life scenarios. After reading this book you will be able to apply image processing techniques and make machine learning models for customized application.
What You Will Learn
- Discover image-processing algorithms and their applications using Python
- Explore image processing using the OpenCV library
- Use TensorFlow, scikit-learn, NumPy, and other libraries
- Work with machine learning and deep learning algorithms for image processing
- Apply image-processing techniques to five real-time projects
Who This Book Is For
Data scientists and software developers interested in image processing and computer vision.
Zielgruppe
Professional/practitioner
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
Chapter 1: Installation and Environment Setup
Chapter 2: Introduction to Python and Image Processing
Chapter 3: Advanced Image Processing using OpenCV
Chapter 4: Machine Learning Approaches in Image Processing
Chapter 5: Real Time Use Cases
Chapter 6: Appendix A