Deep Learning for Vision Systems

Mohamed Elgendy is the technical director at Synapse Technology, a premier AI firm that develops patented computer vision systems to detect threats at security checkpoints throughout the world. Mohamed formerly worked at Amazon as an engineering manager, where he created and taught the deep learning for computer vision course at Amazon's Machine Learning University.

How does a computer learn to recognize what it sees? Deep Learning for Vision Systems provides an answer to this question by using deep learning to computer vision. This book explains the fundamentals of visual intuition using only high school algebra. You will learn how to construct vision system apps for picture production and facial identification using deep learning architectures.

Many cutting-edge developments rely on computer vision, including self-driving cars, drones, augmented reality, facial recognition, and much more. Every day, amazing new computer vision applications are created as a result of rapid breakthroughs in AI and deep learning (DL). Deep Learning for Vision Systems teaches you the principles and methods needed to create intelligent, scalable computer vision systems that can recognize and react to objects in photos, videos, and real-world scenarios. With expert guidance and illustrations of real-world projects from author Mohamed Elgendy, you'll finally grasp cutting-edge deep learning techniques, allowing you to build, contribute to, and lead in the exciting field of computer vision!

Author: Mohamed Elgendy

Link to buy: https://www.amazon.com/Learning-Vision-Systems-Mohamed-Elgendy/dp/1617296198/

Ratings: 4.8 out of 5 stars (from 51 reviews)

Best Sellers Rank: #143,965 in Books

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