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The Resource Practical computer vision applications using deep learning with CNNs : with detailed examples in Python using TensorFlow and Kivy, Ahmed Fawzy Gad

Practical computer vision applications using deep learning with CNNs : with detailed examples in Python using TensorFlow and Kivy, Ahmed Fawzy Gad

Label
Practical computer vision applications using deep learning with CNNs : with detailed examples in Python using TensorFlow and Kivy
Title
Practical computer vision applications using deep learning with CNNs
Title remainder
with detailed examples in Python using TensorFlow and Kivy
Statement of responsibility
Ahmed Fawzy Gad
Creator
Author
Author
Subject
Language
eng
Summary
Deploy deep learning applications into production across multiple platforms. You will work on computer vision applications that use the convolutional neural network (CNN) deep learning model and Python. This book starts by explaining the traditional machine-learning pipeline, where you will analyze an image dataset. Along the way you will cover artificial neural networks (ANNs), building one from scratch in Python, before optimizing it using genetic algorithms. For automating the process, the book highlights the limitations of traditional hand-crafted features for computer vision and why the CNN deep-learning model is the state-of-art solution. CNNs are discussed from scratch to demonstrate how they are different and more efficient than fully connected networks. You will implement a CNN in Python to give you a full understanding of the model. After consolidating the basics, you will use TensorFlow to build a practical image-recognition application and make the pre-trained models accessible over the Internet using Flask. Using Kivy and NumPy, you will create cross-platform data science applications with low overheads. This book will help you apply deep learning and computer vision concepts from scratch, step-by-step from conception to production. You will: Understand how ANNs and CNNs work Create computer vision applications and CNNs from scratch using Python Follow a deep learning project from conception to production using TensorFlow Use NumPy with Kivy to build cross-platform data science applications
Member of
Cataloging source
UPM
http://library.link/vocab/creatorName
Gad, Ahmed Fawzy
Dewey number
006.3
http://bibfra.me/vocab/relation/httpidlocgovvocabularyrelatorsaut
kfu3fclNyyE
Index
no index present
LC call number
Q337.5
LC item number
.G33 2018
Literary form
non fiction
Nature of contents
dictionaries
http://library.link/vocab/subjectName
  • Computer vision
  • Python (Computer program language)
  • Computer programming
  • Artificial Intelligence.
  • Python.
  • Open Source.
Label
Practical computer vision applications using deep learning with CNNs : with detailed examples in Python using TensorFlow and Kivy, Ahmed Fawzy Gad
Instantiates
Publication
Antecedent source
unknown
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
1. Recognition in Computer Vision -- 2. Artificial Neural Network -- 3. Classification using ANN with Engineered Features -- 4. ANN Parameters Optimization -- 5. Convolutional Neural Networks -- 6. TensorFlow Recognition Application -- 7. Deploying Pre-Trained Models -- 8. Cross-Platform Data Science Applications.Appendix: Uploading Projects to PyPI
Dimensions
unknown
Extent
1 online resource
File format
unknown
Form of item
online
Isbn
9781484241660
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
c
Other control number
10.1007/978-1-4842-4167-7
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
  • on1080593231
  • (OCoLC)1080593231
Label
Practical computer vision applications using deep learning with CNNs : with detailed examples in Python using TensorFlow and Kivy, Ahmed Fawzy Gad
Publication
Antecedent source
unknown
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
1. Recognition in Computer Vision -- 2. Artificial Neural Network -- 3. Classification using ANN with Engineered Features -- 4. ANN Parameters Optimization -- 5. Convolutional Neural Networks -- 6. TensorFlow Recognition Application -- 7. Deploying Pre-Trained Models -- 8. Cross-Platform Data Science Applications.Appendix: Uploading Projects to PyPI
Dimensions
unknown
Extent
1 online resource
File format
unknown
Form of item
online
Isbn
9781484241660
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
c
Other control number
10.1007/978-1-4842-4167-7
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
  • on1080593231
  • (OCoLC)1080593231

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