Small Data Learning: Synthetic Data Augmentation for Scarce Scenarios
Machine learning success is often associated with large volumes of data, yet many real-world problems do not have the luxury of abundance. In healthcare diagnostics, industrial quality control, fraud detection, or rare event prediction, data is scarce, sensitive, or expensive to collect. This is where small data learning becomes critical. Instead of waiting for massive […]
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