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Look inside
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!
about the technology
How much has computer vision advanced? One ride in a Tesla is the only answer you’ll need. Deep learning techniques have led to exciting breakthroughs in facial recognition, interactive simulations, and medical imaging, but nothing beats seeing a car respond to real-world stimuli while speeding down the highway.about the book
How does the computer learn to understand what it sees? Deep Learning for Vision Systems answers that by applying deep learning to computer vision. Using only high school algebra, this book illuminates the concepts behind visual intuition. You'll understand how to use deep learning architectures to build vision system applications for image generation and facial recognition.what's inside
- Image classification and object detection
- Advanced deep learning architectures
- Transfer learning and generative adversarial networks
- DeepDream and neural style transfer
- Visual embeddings and image search
From text and object detection to DeepDream and facial recognition...this book is comprehensive, approachable, and relevant for modern applications of deep learning to computer vision systems!
Real-world problem solving without drowning you in details. It elaborates concepts bit by bit, making them easy to assimilate.
An invaluable and comprehensive tour for anyone looking to build real-world vision systems.
Shows you what’s behind modern technologies that allow computers to see things.
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