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Found 3 papers, 1 papers with code
Transfer Learning for Segmentation Problems: Choose the Right Encoder and Skip the Decoder
In this work, we investigate the impact of transfer learning for segmentation problems, being pixel-wise classification problems that can be tackled with encoder-decoder architectures.
Similarity of Pre-trained and Fine-tuned Representations
In transfer learning, only the last part of the networks - the so-called head - is often fine-tuned.
Exploring the Similarity of Representations in Model-Agnostic Meta-Learning
Besides their tremendous success in these tasks, it has still not been fully revealed yet, why it works so well.
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