Image Super Resolution Using Autoencoders in Keras
- Offered byCoursera
Image Super Resolution Using Autoencoders in Keras at Coursera Overview
Image Super Resolution Using Autoencoders in Keras
at Coursera
A comprehensive overview of Image Super Resolution Using Autoencoders in Keras
Duration | 2 hours |
Mode of learning | Online |
Difficulty level | Advanced |
Credential | Certificate |
Image Super Resolution Using Autoencoders in Keras at Coursera Highlights
Image Super Resolution Using Autoencoders in Keras
at Coursera
- Earn a certificate after completion of the course
Image Super Resolution Using Autoencoders in Keras at Coursera Course details
Image Super Resolution Using Autoencoders in Keras
at Coursera
What are the course deliverables?
- Understand what autoencoders are and why they are used
- Design and train an autoencoder to increase the resolution of images with Keras
More about this course
- In this course, you?re going to learn what an autoencoder is, use Keras with Tensorflow as its backend to train your own autoencoder, and use this deep learning powered autoencoder to significantly enhance the quality of images
- That is, our neural network will create high-resolution images from low-res source images
Image Super Resolution Using Autoencoders in Keras at Coursera Curriculum
Image Super Resolution Using Autoencoders in Keras
at Coursera
Project Overview and Import Libraries
What are Autoencoders
Build the Encoder
Build the Decoder to Complete the Network
Create Dataset and Specify Training Routine
Load the Dataset and Pre-trained Model
Model Predictions and Visualizing the Results
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