Abstract Avoiding the risk of undefined categorical labels using nearest-neighbor interpolation overlooks the risk of exacerbating pixel-level annotation errors in augmented training data. Additionally, the inherent low-pass filtering effects of interpolation algorithms exacerbat…
This study systematically benchmarks different data augmentation setups across YOLO26 model size variants to determine the most effective setup for adenovirus detection in TEM images. The benchmarked setups include NAS, GAS, GMAS and DAS, all evaluated under identical training co…