A new fine-grained benchmark dataset of ostracod images shows that existing robust-learning and label-correction methods do not outperform cross-entropy or a naive ensemble baseline.
Hong Kong shallow marine benthic ecosystem history : conservation pale- oecology approach based on microfossil ostracods
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Noisy Ostracods: A Fine-Grained, Imbalanced Real-World Dataset for Benchmarking Robust Machine Learning and Label Correction Methods
A new fine-grained benchmark dataset of ostracod images shows that existing robust-learning and label-correction methods do not outperform cross-entropy or a naive ensemble baseline.