18 citations · 33 across the 3 of their papers we have counts for
3 papers
q-bio.QM2023
Experts' cognition-driven safe noisy labels learning for precise segmentation of residual tumor in breast cancer
Yongquan Yang, Jie Chen, Yani Wei +2
Precise segmentation of residual tumor in breast cancer (PSRTBC) after neoadjuvant chemotherapy is a fundamental key technique in the treatment process of breast cancer. However, a…
cs.LG2021★ 18 cited
One-Step Abductive Multi-Target Learning with Diverse Noisy Samples and Its Application to Tumour Segmentation for Breast Cancer
Yongquan Yang, Fengling Li, Yani Wei +4
Recent studies have demonstrated the effectiveness of the combination of machine learning and logical reasoning, including data-driven logical reasoning, knowledge driven machine l…
cs.LG2020★ 15 cited
Handling Noisy Labels via One-Step Abductive Multi-Target Learning and Its Application to Helicobacter Pylori Segmentation
Yongquan Yang, Yiming Yang, Jie Chen +2
Learning from noisy labels is an important concern in plenty of real-world scenarios. Various approaches for this concern first make corrections corresponding to potentially noisy-…