1 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.CE2023★ 1 cited
ChiMera: Learning with noisy labels by contrasting mixed-up augmentations
Zixuan Liu, Xin Zhang, Junjun He +5
Learning with noisy labels has been studied to address incorrect label annotations in real-world applications. In this paper, we present ChiMera, a two-stage learning-from-noisy-la…
cond-mat.mtrl-sci2023★ 1 cited
Enhanced strength-ductility combination by introducing bimodal grains structures in high-density oxide dispersion strengthened FeCrAl alloys fabricated by spark plasma sintering technology
Xu Yan, Zhifeng Li, Haoxian Yang +1
Oxide dispersion strengthened FeCrAl alloys dispersed high-density nano-oxides in the matrix show outstanding corrosion resistance and mechanical properties. However, ODS FeCrAl al…
eess.IV2023★ 1 cited
AdLER: Adversarial Training with Label Error Rectification for One-Shot Medical Image Segmentation
Xiangyu Zhao, Sheng Wang, Zhiyun Song +5
Accurate automatic segmentation of medical images typically requires large datasets with high-quality annotations, making it less applicable in clinical settings due to limited tra…