Data augmentation: A comprehensive survey of modern approaches

Data augmentation: A comprehensive survey of modern approaches To ensure good performance, modern machine learning models typically require large amounts of quality annotated data. Meanwhile, the data collection and annotation processes are usually performed manually, and consume a lot of time and resources. The quality and representativeness of curated data for a given task is usually dictated by the natural availability of clean data in the particular domain as well as the level of expertise ...