Jiyong Tan

Trustable Co-Label Learning From Multiple Noisy Annotators

2021 · IEEE Transactions on Multimedia

Supervised deep learning depends on massive accurately annotated examples, which is usually impractical in many real-world scenarios. A typical alternative is learning from multiple noisy annotators. Numerous earlier works assume that all labels are noisy, …

A Breast Ultrasound Tumor Detection Framework Using Convolutional Neural Networks

2022

Accurate and efficient breast cancer screening is of great significance to women's health. In order to solve the severe challenges in mass breast screening, such as poor ultrasound image quality, differences in the age and …