Deep Learning for Vision Systems by Mohamed Elgendy (2020, Trade Paperback)
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Deep Learning for Vision Systems by Mohamed Elgendy (2020, Trade Paperback)
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eBay-Artikelnr.:126639105311
Artikelmerkmale
- Artikelzustand
- ISBN
- 9781617296192
Über dieses Produkt
Product Identifiers
Publisher
Manning Publications Co. LLC
ISBN-10
1617296198
ISBN-13
9781617296192
eBay Product ID (ePID)
5038399332
Product Key Features
Number of Pages
480 Pages
Language
English
Publication Name
Deep Learning for Vision Systems
Subject
Computer Graphics, Engineering (General), Intelligence (Ai) & Semantics, Neural Networks
Publication Year
2020
Type
Textbook
Subject Area
Computers, Technology & Engineering
Format
Trade Paperback
Dimensions
Item Height
1.2 in
Item Weight
28 Oz
Item Length
9.2 in
Item Width
7.4 in
Additional Product Features
Intended Audience
Scholarly & Professional
LCCN
2020-303435
Dewey Edition
23
Illustrated
Yes
Dewey Decimal
006.37
Synopsis
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. Summary 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! Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. 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. Table of Contents 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, 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! Key Features · Introduction to computer vision · Deep learning and neural network · Transfer learning and advanced CNN architectures · Image classification and captioning For readers with intermediate Python, math and machine learning skills. About the technology By using deep neural networks, AI systems make decisions based on their perceptions of their input data. Deep learning-based computer vision (CV) techniques, which enhance and interpret visual perceptions, makes tasks like image recognition, generation, and classification possible. Mohamed Elgendy is the head of engineering at Synapse Technology, a leading AI company that builds proprietary computer vision applications to detect threats at security checkpoints worldwide. Previously, Mohamed was an engineering manager at Amazon, where he developed and taught the deep learning for computer vision course at Amazon's Machine Learning University. He also built and managed Amazon's computer vision think tank, among many other noteworthy machine learning accomplishments. Mohamed regularly speaks at many AI conferences like Amazon's DevCon, O'Reilly's AI conference and Google's I/O., 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 Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
LC Classification Number
TA1634.E44 2020
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