Learning on Synthetic Data
Sometimes, we succeed applying transfer learning with relatively few labeled samples to develop custom models. However, there are times when the cost of acquisition is so great that even having a few examples to learn from is difficult. Scientists curate databases like FathomNet to share expertise about the ocean’s wildlife. Applying machine learning to classify marine species is quite challenging in practice due in part to rarity of encounters and challenging photographic environments....