Synthetic Data for Deep Learning: Generate Synthetic Data for Decision Making and Applications with Python and R

Index

A

AlexNet

Algorithmic adaptation

Algorithmic enhancement

Anonymity

Anonymization

Anonymizing data

Archimedean copulas

Artificial intelligence (AI)

Artificial neural networks

Automotive industry

B

Basic functions

Binomial distribution

Bootstrapping

C

C function

Circle without noise

Classification problems

degree of difficulty

with different noise

dimensions

Multi-label

noise control

parameters

samples

with 0.01 separation degree

with 5.0 separation degree

separation degree of classes

class_separation parameters

Clustering problems

make_circles() function

noise levels

numbers of centers

randomly generated

types

cluster_std feature

Computer-generated imagery (CGI)

Computer vision

CNN

digital images

instance segmentation

neural network

Object detection

segmentation problem

visual scenes ...