Deep Learning for Vision Systems you own this product

Mohamed Elgendy
  • October 2020
  • ISBN 9781617296192
  • 480 pages
  • printed in black & white
  • Available translations: Complex Chinese, Korean, Simplified Chinese
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

about the reader

For intermediate Python programmers.

about the author

Mohamed Elgendy is the VP of Engineering at Rakuten. A seasoned AI expert, he has previously built and managed AI products at Amazon and Twilio.

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!

Bojan Djurkovic, DigitalOcean

Real-world problem solving without drowning you in details. It elaborates concepts bit by bit, making them easy to assimilate.

Burhan Ul Haq, Audit XPRT

An invaluable and comprehensive tour for anyone looking to build real-world vision systems.

Richard Vaughan, Purple Monkey Collective

Shows you what’s behind modern technologies that allow computers to see things.

Alessandro Campeis, Vimar
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“Great first book for overall view of computer vision algorithms using deep learning.”
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August 19, 2020 by A Reviewer (AU)
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December 29, 2023 by Seiichiro M. (JP)
“It seemed to me very practical in comparison with other similar books. Above all, in the beginning part, the fundamental principle of hidden layers is well described for intermediate level engineers, who are not familiar with deep-learning techniques.”
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February 28, 2021 by Sm (ON, CA)
“Manning have some good quality books and at decent price. Lot of books are upto date with technology in field like this one. Will be spending next few months reading/building models from this book”
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