更新时间：2021-06-30 18:55:38
coverpage
Title Page
Dedication
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Contributors
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Preface
Who this book is for
What this book covers
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Download the example code files
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Conventions used
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A Fast Introduction to Computer Vision
What constitutes computer vision?
Computer vision is everywhere
Getting started
Reading an image
Image color conversions
Computer vision research conferences
Summary
Libraries Development Platform and Datasets
Libraries and installation
Installing Anaconda
NumPy
Matplotlib
SciPy
Jupyter notebook
Installing OpenCV
OpenCV Anaconda installation
OpenCV build from source
Opencv FAQs
TensorFlow for deep learning
Keras for deep learning
Datasets
ImageNet
MNIST
CIFAR-10
Pascal VOC
MSCOCO
TUM RGB-D dataset
References
Image Filtering and Transformations in OpenCV
Datasets and libraries required
Image manipulation
Introduction to filters
Linear filters
2D linear filters
Box filters
Properties of linear filters
Non-linear filters
Smoothing a photo
Histogram equalization
Median filter
Image gradients
Transformation of an image
Translation
Rotation
Affine transform
Image pyramids
What is a Feature?
Features use cases
Datasets and libraries
Why are features important?
Harris Corner Detection
FAST features
ORB features
FAST feature limitations
BRIEF Descriptors and their limitations
ORB features using OpenCV
The black box feature
Application – find your object in an image
Applications – is it similar?
Convolutional Neural Networks
Datasets and libraries used
Introduction to neural networks
A simple neural network
Revisiting the convolution operation
The convolution layer
The activation layer
The pooling layer
The fully connected layer
Batch Normalization
Dropout
CNN in practice
Fashion-MNIST classifier training code
Analysis of CNNs
Popular CNN architectures
VGGNet
