347 citations · 610 across the 24 of their papers we have counts for
7 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…
Transcending XAI Algorithm Boundaries through End-User-Inspired Design
Weina Jin, Jianyu Fan, Diane Gromala +3
The boundaries of existing explainable artificial intelligence (XAI) algorithms are confined to problems grounded in technical users' demand for explainability. This research parad…
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…
Federated Learning from Only Unlabeled Data with Class-Conditional-Sharing Clients
Nan Lu, Zhao Wang, Xiaoxiao Li +3
Supervised federated learning (FL) enables multiple clients to share the trained model without sharing their labeled data. However, potential clients might even be reluctant to lab…
RestoreDet: Degradation Equivariant Representation for Object Detection in Low Resolution Images
Ziteng Cui, Yingying Zhu, Lin Gu +5
Image restoration algorithms such as super resolution (SR) are indispensable pre-processing modules for object detection in degraded images. However, most of these algorithms assum…