347 citations · 610 across the 24 of their papers we have counts for
6 papers · 1 filter
Exploring Resolution and Degradation Clues as Self-supervised Signal for Low Quality Object Detection
Ziteng Cui, Yingying Zhu, Lin Gu +5
Image restoration algorithms such as super resolution (SR) are indispensable pre-processing modules for object detection in low quality images. Most of these algorithms assume the…
Backdoor Attack is a Devil in Federated GAN-based Medical Image Synthesis
Ruinan Jin, Xiaoxiao Li
Deep Learning-based image synthesis techniques have been applied in healthcare research for generating medical images to support open research. Training generative adversarial neur…
Class Impression for Data-free Incremental Learning
Sana Ayromlou, Purang Abolmaesumi, Teresa Tsang +1
Standard deep learning-based classification approaches require collecting all samples from all classes in advance and are trained offline. This paradigm may not be practical in rea…
Dynamic Bank Learning for Semi-supervised Federated Image Diagnosis with Class Imbalance
Meirui Jiang, Hongzheng Yang, Xiaoxiao Li +3
Despite recent progress on semi-supervised federated learning (FL) for medical image diagnosis, the problem of imbalanced class distributions among unlabeled clients is still unsol…
Leveraging Human Selective Attention for Medical Image Analysis with Limited Training Data
Yifei Huang, Xiaoxiao Li, Lijin Yang +6
The human gaze is a cost-efficient physiological data that reveals human underlying attentional patterns. The selective attention mechanism helps the cognition system focus on task…
One Map Does Not Fit All: Evaluating Saliency Map Explanation on Multi-Modal Medical Images
Weina Jin, Xiaoxiao Li, Ghassan Hamarneh
Being able to explain the prediction to clinical end-users is a necessity to leverage the power of AI models for clinical decision support. For medical images, saliency maps are th…