AI, Machine learning and Deep learning with self driving cars (dr.ibrahim sobh)

1. Study Machine learning:
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Basics: Machine Learning:
https://www.coursera.org/learn/machine-learning
Deep Learning Specialization:
https://www.coursera.org/specializations/deep-learning
Convolutional Neural Networks for Visual Recognition:
http://cs231n.stanford.edu/
http://karpathy.github.io/
MIT 6.S094: Deep Learning for Self-Driving Cars:
https://selfdrivingcars.mit.edu
(Reference) Deep Learning, MIT Press book, Ian Goodfellow and Yoshua Bengio and Aaron Courville,
https://www.deeplearningbook.org/
(Reference) Neural Networks for Machine Learning:
https://www.coursera.org/learn/neural-
networks
Self Driving:
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Drive4U in Paris
https://youtu.be/9mBLl6JuvsM
Society of Automotive Engineers (SAE)
https://www.sae.org/news/2019/01/sae-updates-j3016-automated-driving-graphic
Critical Reasons for Crashes https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/812115

2. GANs
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GANs for image to image translation:
https://github.com/mingyuliutw/UNIT
https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix
Related Papers:
Unsupervised Neural Sensor Models for Synthetic LiDAR Data Augmentation
https://ml4ad.github.io/files/papers/Unsupervised%20Neural%20Sensor%20Models%20for%20Syntheti
c%20LiDAR%20Data%20Augmentation.pdf
LiDAR Sensor modeling and Data augmentation with GANs for Autonomous driving
https://drive.google.com/file/d/1sQIkTTRxlb8HLTZFac-saB-UluIuWSXX/view
Yes, we GAN: Applying Adversarial Techniques for Autonomous Driving
https://arxiv.org/abs/1902.03442
Adversarial Attacks and defenses
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Explaining and Harnessing Adversarial Examples
https://arxiv.org/abs/1412.6572
Adversarial Patch
https://arxiv.org/abs/1712.09665
https://openai.com/blog/robust-adversarial-inputs/
Adversarial Objects Against LiDAR-Based Autonomous Driving Systems
https://arxiv.org/abs/1907.05418
Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks
https://arxiv.org/abs/1704.01155
Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks
https://arxiv.org/abs/1511.04508