Here goes my next Keras Example all about implementing Swin Transformers, a general-purpose backbone for computer vision. The Swin Transformer architecture for image classification – a Transformer-based vision model that uses local self-attention as a way to make self-attention on images linear in complexity. I go on to demonstrate using this for image classification on CIFAR-100.
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PS: After your wonderful suggestion, @lgusm , I am already in works to publish the trained model on TF Hub.
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That’s great!!! thanks!
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How would I use my own small dataset for binary classification and not the cifra-100 dataset?
Additional to this and CNN, what other image classification algorithms are in Tensorflow?