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Encoder decoder architectures
A video giving an overview of how encoder-decoder architectures work, and some common examples
A common approach to extracting spatial features from images are so-called encoder-decoder architectures.
While classification networks aim to take the information in an image and compress it down to a perhaps a single number that represents an image class, other tasks such as image segmentation instead look to label every pixel in the image in some way.
A common way of achieving this via deep learning is through the use of encoder-decoder networks, as we will see in this video.
