Large-scale pretraining on pathological images for fine-tuning of small pathological benchmarks

Understand

Pretraining a deep learning model on large image datasets is a standard step before fine-tuning the model on small targeted datasets.

• The large dataset is usually general images (e.g.
• imagenet2012) while the small dataset can be specialized datasets that have different distributions from the large dataset.
• However, this 'large-to-small' strategy is not well-validated when the large dataset is specialized and has a similar distribution to small datasets.