Zeju Li

Orcid: 0000-0002-4608-2959

According to our database1, Zeju Li authored at least 39 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Layer-Sensitive Neural Processing Architecture for Error-Tolerant Applications.
IEEE Trans. Very Large Scale Integr. Syst., May, 2024

Exploring the Distributed Knowledge Congruence in Proxy-data-free Federated Distillation.
ACM Trans. Intell. Syst. Technol., April, 2024

Learning Label Refinement and Threshold Adjustment for Imbalanced Semi-Supervised Learning.
CoRR, 2024

3DMIT: 3D Multi-modal Instruction Tuning for Scene Understanding.
CoRR, 2024

3DMIT: 3D Multi-Modal Instruction Tuning for Scene Understanding.
Proceedings of the IEEE International Conference on Multimedia and Expo, 2024

2023
Joint Optimization of Class-Specific Training- and Test-Time Data Augmentation in Segmentation.
IEEE Trans. Medical Imaging, November, 2023

SemProtector: A Unified Framework for Semantic Protection in Deep Learning-based Semantic Communication Systems.
IEEE Commun. Mag., November, 2023

W-AMA: Weight-aware Approximate Multiplication Architecture for neural processing.
Comput. Electr. Eng., October, 2023

Context Label Learning: Improving Background Class Representations in Semantic Segmentation.
IEEE Trans. Medical Imaging, June, 2023

Causality-Inspired Single-Source Domain Generalization for Medical Image Segmentation.
IEEE Trans. Medical Imaging, April, 2023

Learn2Reg: Comprehensive Multi-Task Medical Image Registration Challenge, Dataset and Evaluation in the Era of Deep Learning.
IEEE Trans. Medical Imaging, March, 2023

Post-Deployment Adaptation with Access to Source Data via Federated Learning and Source-Target Remote Gradient Alignment.
Proceedings of the Machine Learning in Medical Imaging - 14th International Workshop, 2023

Robust Segmentation via Topology Violation Detection and Feature Synthesis.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Robustness Stress Testing in Medical Image Classification.
Proceedings of the Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, 2023

Boosting Physical Layer Black-Box Attacks with Semantic Adversaries in Semantic Communications.
Proceedings of the IEEE International Conference on Communications, 2023

Multi-Source Education Knowledge Graph Construction and Fusion for College Curricula.
Proceedings of the IEEE International Conference on Advanced Learning Technologies, 2023

2022
Breast Tumor Classification Based on MRI-US Images by Disentangling Modality Features.
IEEE J. Biomed. Health Informatics, 2022

Author Correction: Federated deep learning for detecting COVID-19 lung abnormalities in CT: a privacy-preserving multinational validation study.
npj Digit. Medicine, 2022

Enhancing MR image segmentation with realistic adversarial data augmentation.
Medical Image Anal., 2022

SemBAT: Physical Layer Black-box Adversarial Attacks for Deep Learning-based Semantic Communication Systems.
Proceedings of the 96th Vehicular Technology Conference, 2022

Improved Post-hoc Probability Calibration for Out-of-Domain MRI Segmentation.
Proceedings of the Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, 2022

Fetal Cortex Segmentation with Topology and Thickness Loss Constraints.
Proceedings of the Ethical and Philosophical Issues in Medical Imaging, Multimodal Learning and Fusion Across Scales for Clinical Decision Support, and Topological Data Analysis for Biomedical Imaging, 2022

Estimating Model Performance Under Domain Shifts with Class-Specific Confidence Scores.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

MaxStyle: Adversarial Style Composition for Robust Medical Image Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

Tackling Long-Tailed Category Distribution Under Domain Shifts.
Proceedings of the Computer Vision - ECCV 2022, 2022

2021
Analyzing Overfitting Under Class Imbalance in Neural Networks for Image Segmentation.
IEEE Trans. Medical Imaging, 2021

DeepVolume: Brain Structure and Spatial Connection-Aware Network for Brain MRI Super-Resolution.
IEEE Trans. Cybern., 2021

Federated deep learning for detecting COVID-19 lung abnormalities in CT: a privacy-preserving multinational validation study.
npj Digit. Medicine, 2021

Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning.
CoRR, 2021

2020
High-Resolution Chest X-Ray Bone Suppression Using Unpaired CT Structural Priors.
IEEE Trans. Medical Imaging, 2020

2019
Super-Resolution Reconstruction of Plane-Wave Ultrasound Image Based on a Multi-Angle Parallel U-Net with Maxout Unit and Novel Loss Function.
J. Medical Imaging Health Informatics, 2019

Early identification of ischemic stroke in noncontrast computed tomography.
Biomed. Signal Process. Control., 2019

Deep Generative Adversarial Networks for Thin-Section Infant MR Image Reconstruction.
IEEE Access, 2019

Encoding CT Anatomy Knowledge for Unpaired Chest X-ray Image Decomposition.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

Overfitting of Neural Nets Under Class Imbalance: Analysis and Improvements for Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

2018
Left Ventricle Segmentation via Optical-Flow-Net from Short-Axis Cine MRI: Preserving the Temporal Coherence of Cardiac Motion.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018

A Multi-Scope Convolutional Neural Network for Automatic Left Ventricle Segmentation from Magnetic Resonance Images: Deep-Learning at Multiple Scopes.
Proceedings of the 11th International Congress on Image and Signal Processing, 2018

2017
Brain Tumor Segmentation Using an Adversarial Network.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2017

Reconstruction of Thin-Slice Medical Images Using Generative Adversarial Network.
Proceedings of the Machine Learning in Medical Imaging - 8th International Workshop, 2017


  Loading...