Hands-On Computer Vision with TensorFlow 2

Hands-On Computer Vision with TensorFlow 2

Author: Benjamin Planche

Publisher: Packt Publishing Ltd

ISBN: 9781788839266

Category: Computers

Page: 372

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A practical guide to building high performance systems for object detection, segmentation, video processing, smartphone applications, and more Key FeaturesDiscover how to build, train, and serve your own deep neural networks with TensorFlow 2 and KerasApply modern solutions to a wide range of applications such as object detection and video analysisLearn how to run your models on mobile devices and web pages and improve their performanceBook Description Computer vision solutions are becoming increasingly common, making their way into fields such as health, automobile, social media, and robotics. This book will help you explore TensorFlow 2, the brand new version of Google's open source framework for machine learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks. Hands-On Computer Vision with TensorFlow 2 starts with the fundamentals of computer vision and deep learning, teaching you how to build a neural network from scratch. You will discover the features that have made TensorFlow the most widely used AI library, along with its intuitive Keras interface. You'll then move on to building, training, and deploying CNNs efficiently. Complete with concrete code examples, the book demonstrates how to classify images with modern solutions, such as Inception and ResNet, and extract specific content using You Only Look Once (YOLO), Mask R-CNN, and U-Net. You will also build generative adversarial networks (GANs) and variational autoencoders (VAEs) to create and edit images, and long short-term memory networks (LSTMs) to analyze videos. In the process, you will acquire advanced insights into transfer learning, data augmentation, domain adaptation, and mobile and web deployment, among other key concepts. By the end of the book, you will have both the theoretical understanding and practical skills to solve advanced computer vision problems with TensorFlow 2.0. What you will learnCreate your own neural networks from scratchClassify images with modern architectures including Inception and ResNetDetect and segment objects in images with YOLO, Mask R-CNN, and U-NetTackle problems faced when developing self-driving cars and facial emotion recognition systemsBoost your application's performance with transfer learning, GANs, and domain adaptationUse recurrent neural networks (RNNs) for video analysisOptimize and deploy your networks on mobile devices and in the browserWho this book is for If you're new to deep learning and have some background in Python programming and image processing, like reading/writing image files and editing pixels, this book is for you. Even if you're an expert curious about the new TensorFlow 2 features, you'll find this book useful. While some theoretical concepts require knowledge of algebra and calculus, the book covers concrete examples focused on practical applications such as visual recognition for self-driving cars and smartphone apps.
Hands-On Computer Vision with TensorFlow 2
Language: en
Pages: 372
Authors: Benjamin Planche, Eliot Andres
Categories: Computers
Type: BOOK - Published: 2019-05-30 - Publisher: Packt Publishing Ltd

A practical guide to building high performance systems for object detection, segmentation, video processing, smartphone applications, and more Key FeaturesDiscover how to build, train, and serve your own deep neural networks with TensorFlow 2 and KerasApply modern solutions to a wide range of applications such as object detection and video
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Language: en
Pages: 202
Authors: Dmitrijs Cudihins
Categories: Computers
Type: BOOK - Published: 2018-06-29 - Publisher: Packt Publishing Ltd

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Language: en
Pages:
Authors: Rajeev Ratan
Categories: Computers
Type: BOOK - Published: 2020 - Publisher:

Build your own computer vision deep learning classifiers About This Video Gain a solid understanding of core computer vision concepts using OpenCV, and utilize deep learning to create advanced computer vision models Learn quickly without being bogged down by complex mathematical theory Use the latest libraries including the latest version
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Language: en
Pages: 260
Authors: Klevis Ramo
Categories: Computers
Type: BOOK - Published: 2019-02-21 - Publisher: Packt Publishing Ltd

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Language: en
Pages: 380
Authors: Bhaumik Vaidya
Categories: Computers
Type: BOOK - Published: 2018-09-26 - Publisher: Packt Publishing Ltd

Discover how CUDA allows OpenCV to handle complex and rapidly growing image data processing in computer and machine vision by accessing the power of GPU Key FeaturesExplore examples to leverage the GPU processing power with OpenCV and CUDAEnhance the performance of algorithms on embedded hardware platformsDiscover C++ and Python libraries