Indirectly, we have already presented how standard pretrained models provided through TensorFlow Hub and Keras applications can be fetched and easily transformed into feature extractors for new tasks. However, it is also common to reuse non-standard networks; for example, more specific state-of-the-art CNNs provided by experts, or custom models already trained for some previous tasks. We will demonstrate how any models can be edited for transfer learning.
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