Name
Title | ||
|---|---|---|
Joint Semi-supervised and Active Learning for Segmentation of Gigapixel Pathology Images with Cost-Effective Labeling |
Abstract | ||
|---|---|---|
The need for manual and detailed annotations limits the applicability of supervised deep learning algorithms in medical image analyses, specifically in the field of pathology. Semi-supervised learning (SSL) provides an effective way for leveraging unlabeled data to relieve the heavy reliance on the amount of labeled samples when training a model. Although SSL has shown good performance, the perfor... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ICCVW54120.2021.00072 | 2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW) |
Keywords | DocType | Volume |
Training,Deep learning,Pathology,Image segmentation,Image analysis,Conferences,Manuals | Conference | 2021 |
Issue | ISSN | ISBN |
1 | 2473-9936 | 978-1-6654-0191-3 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhengfeng Lai | 1 | 0 | 0.68 |
| Chao Wang | 2 | 895 | 190.04 |
| Luca Cerny Oliveira | 3 | 0 | 1.35 |
| Brittany N. Dugger | 4 | 0 | 1.35 |
| Sen-Ching S. Cheung | 5 | 776 | 70.97 |
| Chen-Nee Chuah | 6 | 2006 | 161.34 |