Computer vision using deep learning : neural network architectures with Python and Keras / Vaibhav Verdhan.
2021
TA1634
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Details
Title
Computer vision using deep learning : neural network architectures with Python and Keras / Vaibhav Verdhan.
Author
Verdhan, Vaibhav, author.
ISBN
9781484266168 (electronic bk.)
1484266161 (electronic bk.)
1484266153
9781484266151
1484266161 (electronic bk.)
1484266153
9781484266151
Published
[Berkeley, Calif.] : Apress, [2021]
Language
English
Description
1 online resource
Other Standard Identifiers
10.1007/978-1-4842-6616-8 doi
Call Number
TA1634
Dewey Decimal Classification
006.3/7
Summary
Organizations spend huge resources in developing software that can perform the way a human does. Image classification, object detection and tracking, pose estimation, facial recognition, and sentiment estimation all play a major role in solving computer vision problems. This book will bring into focus these and other deep learning architectures and techniques to help you create solutions using Keras and the TensorFlow library. You'll also review mutliple neural network architectures, including LeNet, AlexNet, VGG, Inception, R-CNN, Fast R-CNN, Faster R-CNN, Mask R-CNN, YOLO, and SqueezeNet and see how they work alongside Python code via best practices, tips, tricks, shortcuts, and pitfalls. All code snippets will be broken down and discussed thoroughly so you can implement the same principles in your respective environments. Computer Vision Using Deep Learning offers a comprehensive yet succinct guide that stitches DL and CV together to automate operations, reduce human intervention, increase capability, and cut the costs. You will: Examine deep learning code and concepts to apply guiding principles to your own projects Classify and evaluate various architectures to better understand your options in various use cases Go behind the scenes of basic deep learning functions to find out how they work.
Bibliography, etc. Note
Includes bibliographical references and index.
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Access limited to authorized users.
Digital File Characteristics
text file
PDF
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed March 22, 2021).
Available in Other Form
Computer vision using deep learning.
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Table of Contents
Chapter 1 Introduction to Computer Vision and Deep Learning
Chapter 2 Nuts and Bolts of Deep Learning for Computer Vision
Chapter 3 Image Classification using LeNet
Chapter 4 VGGNet and AlexNext Networks
Chapter 5 Object Detection Using Deep Learning
Chapter 6 Facial Recognition and Gesture Recognition
Chapter 7 Video Analytics Using Deep Learning
Chapter 8 End-to-end Model Development
Appendix.
Chapter 2 Nuts and Bolts of Deep Learning for Computer Vision
Chapter 3 Image Classification using LeNet
Chapter 4 VGGNet and AlexNext Networks
Chapter 5 Object Detection Using Deep Learning
Chapter 6 Facial Recognition and Gesture Recognition
Chapter 7 Video Analytics Using Deep Learning
Chapter 8 End-to-end Model Development
Appendix.