6 citations · 12 across the 3 of their papers we have counts for
3 papers
cs.CV2022★ 6 cited
Neighborhood Collective Estimation for Noisy Label Identification and Correction
Jichang Li, Guanbin Li, Feng Liu +1
Learning with noisy labels (LNL) aims at designing strategies to improve model performance and generalization by mitigating the effects of model overfitting to noisy labels. The ke…
cs.CV2022★ 5 cited
Centrality and Consistency: Two-Stage Clean Samples Identification for Learning with Instance-Dependent Noisy Labels
Ganlong Zhao, Guanbin Li, Yipeng Qin +2
Deep models trained with noisy labels are prone to over-fitting and struggle in generalization. Most existing solutions are based on an ideal assumption that the label noise is cla…
eess.IV2020★ 1 cited
Segmentation-based Method combined with Dynamic Programming for Brain Midline Delineation
Shen Wang, Kongming Liang, Chengwei Pan +5
The midline related pathological image features are crucial for evaluating the severity of brain compression caused by stroke or traumatic brain injury (TBI). The automated midline…