1 code implementation • 30 Apr 2022 • Yaoru Luo, Guole Liu, Yuanhao Guo, Ge Yang
Our understanding of the learning behavior of DNNs trained by noisy segmentation labels remains limited.
no code implementations • 18 Feb 2022 • Huihui Fang, Fei Li, Junde Wu, Huazhu Fu, Xu sun, Jaemin Son, Shuang Yu, Menglu Zhang, Chenglang Yuan, Cheng Bian, Baiying Lei, Benjian Zhao, Xinxing Xu, Shaohua Li, Francisco Fumero, José Sigut, Haidar Almubarak, Yakoub Bazi, Yuanhao Guo, Yating Zhou, Ujjwal Baid, Shubham Innani, Tianjiao Guo, Jie Yang, José Ignacio Orlando, Hrvoje Bogunović, Xiulan Zhang, Yanwu Xu
Here we release a multi-annotation, multi-quality, and multi-device color fundus image dataset for glaucoma analysis on an original challenge -- Retinal Fundus Glaucoma Challenge 2nd Edition (REFUGE2).
no code implementations • 22 Mar 2021 • Yaoru Luo, Guole Liu, Yuanhao Guo, Ge Yang
When trained with these noisy labels, DNNs provide largely the same segmentation performance as trained by the original ground truth.
1 code implementation • 13 Jul 2020 • Cong Chen, Shouyang Dong, Ye Tian, Kunlin Cao, Li Liu, Yuanhao Guo
(1) The teacher model serves a dual role as a teacher and a student, such that the teacher predictions on unlabeled images may be very close to those of student, which limits the upper-bound of the student.
1 code implementation • 30 Oct 2019 • Yuanhao Guo, Fons J. Verbeek, Ge Yang
Robust and accurate camera calibration is essential for 3D reconstruction in light microscopy under circular motion.