Deep Learning for Vision Systems

Deep Learning for Vision Systems
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Book Description
Computer vision is central to many leading-edge innovations, including self-driving cars, drones, augmented reality, facial recognition, and much, much more. Amazing new computer vision applications are developed every day, thanks to rapid advances in AI and deep learning (DL).

Deep Learning for Vision Systems teaches you the concepts and tools for building intelligent, scalable computer vision systems that can identify and react to objects in images, videos, and real life. With author Mohamed Elgendy's expert instruction and illustration of real-world projects, you'll finally grok state-of-the-art deep learning techniques, so you can build, contribute to, and lead in the exciting realm of computer vision!

Content

PART 1 - DEEP LEARNING FOUNDATION
1. Welcome to computer vision
2. Deep learning and neural networks
3. Convolutional neural networks
4. Structuring DL projects and hyperparameter tuning

PART 2 - IMAGE CLASSIFICATION AND DETECTION
5. Advanced CNN architectures
6. Transfer learning
7. Object detection with R-CNN, SSD, and YOLO

PART 3 - GENERATIVE MODELS AND VISUAL EMBEDDINGS
8. Generative adversarial networks (GANs)
9. DeepDream and neural style transfer
10. Visual embeddings

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