Ebook: Deep Learning for Vision Systems
Author: Mohamed Elgendy
- Genre: Computers // Cybernetics: Artificial Intelligence
- Tags: Deep Learning, Computer Vision, Image Processing, Recommender Systems, Convolutional Neural Networks, Generative Adversarial Networks, Face Recognition, Classification, Transfer Learning, Feature Engineering, Pipelines, Gradient Descent, Regularization, Hyperparameter Tuning, Optimization, Perception, Perceptron, Image Classification, Overfitting, Inception Networks, Activation Functions, AlexNet, LeNet, GoogLeNet, ResNet, VGGNet, Object Detection, Backpropagation, Datasets, Generative Art, Feedforward Neural Networks
- Year: 2020
- Publisher: Manning Publications
- City: Shelter Island, NY
- Edition: 1
- Language: English
- pdf
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.
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.
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