10 citations · 10 across the 3 of their papers we have counts for
3 papers
eess.IV2023★ 10 cited
Domain Generalization in Computational Pathology: Survey and Guidelines
Mostafa Jahanifar, Manahil Raza, Kesi Xu +8
Deep learning models have exhibited exceptional effectiveness in Computational Pathology (CPath) by tackling intricate tasks across an array of histology image analysis application…
eess.IV2023
MoMA: Momentum Contrastive Learning with Multi-head Attention-based Knowledge Distillation for Histopathology Image Analysis
Trinh Thi Le Vuong, Jin Tae Kwak
There is no doubt that advanced artificial intelligence models and high quality data are the keys to success in developing computational pathology tools. Although the overall volum…
cs.CV2022
IMPaSh: A Novel Domain-shift Resistant Representation for Colorectal Cancer Tissue Classification
Trinh Thi Le Vuong, Quoc Dang Vu, Mostafa Jahanifar +3
The appearance of histopathology images depends on tissue type, staining and digitization procedure. These vary from source to source and are the potential causes for domain-shift…