6 citations · 6 across the 5 of their papers we have counts for
7 papers
Domain Adaptive Cascade R-CNN for MItosis DOmain Generalization (MIDOG) Challenge
Xi Long, Ying Cheng, Xiao Mu +2
We present a summary of the domain adaptive cascade R-CNN method for mitosis detection of digital histopathology images. By comprehensive data augmentation and adapting existing po…
Class-Aware Domain Adaptation for Improving Adversarial Robustness
Xianxu Hou, Jingxin Liu, Bolei Xu +3
Recent works have demonstrated convolutional neural networks are vulnerable to adversarial examples, i.e., inputs to machine learning models that an attacker has intentionally desi…
Dual Adaptive Pyramid Network for Cross-Stain Histopathology Image Segmentation
Xianxu Hou, Jingxin Liu, Bolei Xu +6
Supervised semantic segmentation normally assumes the test data being in a similar data domain as the training data. However, in practice, the domain mismatch between the training…
Pathological Myopic Image Analysis with Transfer Learning
Ruitao Xie, Libo Liu, Jingxin Liu +1
We present a summary of transfer learning based methods for several challenging myopic fundus image analysis tasks including classification of pathological and non-pathological myo…
Learning Deep Image Priors for Blind Image Denoising
Xianxu Hou, Hongming Luo, Jingxin Liu +5
Image denoising is the process of removing noise from noisy images, which is an image domain transferring task, i.e., from a single or several noise level domains to a photo-realis…
Look, Investigate, and Classify: A Deep Hybrid Attention Method for Breast Cancer Classification
Bolei Xu, Jingxin Liu, Xianxu Hou +6
One issue with computer based histopathology image analysis is that the size of the raw image is usually very large. Taking the raw image as input to the deep learning model would…