Image Classification on CIFAR-10-N-LT Imbalance Ratio 10 (Noise Robustness) benchmark leaderboard · SOTA2 Research

Image Classification on CIFAR-10-N-LT Imbalance Ratio 10 (Noise Robustness)

0.8944Accuracy (NR 0.1)Dynamic Loss

Evaluation Results

Method	Links
Dynamic Loss2022.11		0.8944	0.8846	0.8672	0.8473	0.8371	0.8055
Dynamic Loss2022.11		0.8923	0.8839	0.8658	0.8443	0.8334	0.7973
DivideMix + Balanced-Softmax2022.11		0.8893	0.8606	0.7919	0.7981	0.782	0.7275
DivideMix2022.11		0.885	0.8713	0.6767	0.7426	0.7415	0.6074
DivideMix + Balanced-Softmax2022.11		0.8823	0.8696	0.7802	0.7917	0.7689	0.716
DivideMix2022.11		0.8811	0.8695	0.6642	0.7378	0.7385	0.5819
Balanced-Softmax2022.11		0.8762	0.845	0.8284	0.7909	0.759	0.7637
Balanced-Softmax2022.11		0.8752	0.84	0.7949	0.7353	0.6527	0.6966
ELR+2022.11		0.8704	0.8614	0.8438	0.833	0.8023	0.7034
HAR2022.11		0.8703	0.8447	0.8194	0.7987	0.7825	0.7717
MOIT+2022.11		0.87	0.8484	0.8485	0.8195	0.7952	0.6848
MOIT+2022.11		0.8667	0.846	0.8485	0.8134	0.7902	0.6811
HAR2022.11		0.8646	0.8427	0.8178	0.7955	0.7807	0.7652
ELR+2022.11		0.8521	0.8571	0.8413	0.8116	0.7891	0.6931
CurveNet2022.11		0.8487	0.8462	0.7998	0.8133	0.7837	0.7136
CurveNet2022.11		0.841	0.817	0.7847	0.7873	0.7565	0.6936
FaMUS2022.11		0.8312	0.8434	0.8485	0.8544	0.8412	0.6666
FaMUS2022.11		0.7731	0.7868	0.7915	0.8117	0.7757	0.6153
Cross Entropy2022.11		0.7714	0.7435	0.7222	0.6828	0.5965	0.6043
Cross Entropy2022.11		0.7663	0.6889	0.6121	0.5401	0.4409	0.5273