Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
2 Hour(s) 31 Minute(s)
Language
English
Taught by
Brad Klingensmith
Certificate
- Available
- *The delivery and distribution of the certificate are subject to the policies and arrangements of the course provider.
Rating
5 views
Course Overview
Enhance/upsample images with Generative Adversarial Networks using Python and Tensorflow 2.0
We've all seen the gimmick in crime TV shows where the investigators manage to take a tiny patch of an image and magnify it with unrealistic clarity. Well today, Generative Adversarial Networks are making the impossible possible.
Dive into this course where I’ll show you how easily we can take the fundamentals from my High Resolution Generative Adversarial Networks course and build on this to accomplish this impressive feat known as Super-resolution. Not only will you be able to train a Generator to magnify an image to 4 times it’s original size (that’s 16 times the number of pixel!), but it will take relatively little effort on our end.
Just as in the first course, we’ll use Python and TensorFlow 2.0 along with Keras to build and train our convolutional neural networks. And since training our networks will require a ton of computational power, we’ll once again use Google CoLab to connect to a free Cloud TPU. This will allow us to complete the training in just a few days without spending anything on hardware!
If this sounds enticing, take a few minutes to watch the free preview of the “Results!” lesson. I have no doubt that you will come away impressed.
Course Content
- 4 section(s)
- 24 lecture(s)
- Section 1 Introduction
- Section 2 Model Architecture
- Section 3 Training
- Section 4 Super-resolution in Action!
What You’ll Learn
- Create a generator architecture that upsamples an image by 4 times in each dimension
- Create a discriminator architecture that scores both realism and fidelity to the original image
- Modify custom written Keras layers to accept input images of any size without rebuilding the model
- Train the models on a Cloud TPU through Google CoLab
- Use the trained generator in a practical application to upsample your own images
Reviews
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MMalak Soni
No explanation, just an quick overview about the SRGAN, I have started running the Collab Notebook hope i will get results after 65hours.
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AArie Meirovich
There is a need for a more elaborate description of the algorithm and a comprehensive overview of the software architecture.
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MMohammad Rafiei
Fantastic job in both courses; I highly recommend students with intermediate machine learning expertise (with a TensorFlow focus) to take the two courses (as of Jan 2023) by Brad Klingensmith.
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TTanzim
The course content is amazing! The instructor is knowledgeable and very quick in response. Best instructor on Udemy ever!
