1 citations · 1 across the 8 of their papers we have counts for
8 papers
3DMIT: 3D Multi-modal Instruction Tuning for Scene Understanding
Zeju Li, Chao Zhang, Xiaoyan Wang +4
The remarkable potential of multi-modal large language models (MLLMs) in comprehending both vision and language information has been widely acknowledged. However, the scarcity of 3…
Robustness Stress Testing in Medical Image Classification
Mobarakol Islam, Zeju Li, Ben Glocker
Deep neural networks have shown impressive performance for image-based disease detection. Performance is commonly evaluated through clinical validation on independent test sets to…
SemProtector: A Unified Framework for Semantic Protection in Deep Learning-based Semantic Communication Systems
Xinghan Liu, Guoshun Nan, Qimei Cui +6
Recently proliferated semantic communications (SC) aim at effectively transmitting the semantics conveyed by the source and accurately interpreting the meaning at the destination.…
Post-Deployment Adaptation with Access to Source Data via Federated Learning and Source-Target Remote Gradient Alignment
Felix Wagner, Zeju Li, Pramit Saha +1
Deployment of Deep Neural Networks in medical imaging is hindered by distribution shift between training data and data processed after deployment, causing performance degradation.…
Joint Optimization of Class-Specific Training- and Test-Time Data Augmentation in Segmentation
Zeju Li, Konstantinos Kamnitsas, Qi Dou +2
This paper presents an effective and general data augmentation framework for medical image segmentation. We adopt a computationally efficient and data-efficient gradient-based meta…
Boosting Physical Layer Black-Box Attacks with Semantic Adversaries in Semantic Communications
Zeju Li, Xinghan Liu, Guoshun Nan +4
End-to-end semantic communication (ESC) system is able to improve communication efficiency by only transmitting the semantics of the input rather than raw bits. Although promising,…