b'Hongwei Li'

research

∙ 08/28/2023

A Comprehensive Overview of Backdoor Attacks in Large Language Models within Communication Networks

The Large Language Models (LLMs) are poised to offer efficient and intel...

0 Haomiao Yang, et al. ∙

research

∙ 06/07/2023

Extracting Cloud-based Model with Prior Knowledge

Machine Learning-as-a-Service, a pay-as-you-go business pattern, is wide...

0 Shiqian Zhao, et al. ∙

research

∙ 05/11/2023

SigRec: Automatic Recovery of Function Signatures in Smart Contracts

Millions of smart contracts have been deployed onto Ethereum for providi...

0 Ting Chen, et al. ∙

research

∙ 01/17/2023

Quantified Canine: Inferring Dog Personality From Wearables

Being able to assess dog personality can be used to, for example, match ...

0 Lakmal Meegahapola, et al. ∙

research

∙ 12/16/2022

Neural Implicit k-Space for Binning-free Non-Cartesian Cardiac MR Imaging

In this work, we propose a novel image reconstruction framework that dir...

0 Wenqi Huang, et al. ∙

research

∙ 12/03/2022

Efficiency Boosting of Secure Cross-platform Recommender Systems over Sparse Data

Fueled by its successful commercialization, the recommender system (RS) ...

0 Hao Ren, et al. ∙

research

∙ 10/16/2022

STAR: Zero-Shot Chinese Character Recognition with Stroke- and Radical-Level Decompositions

Zero-shot Chinese character recognition has attracted rising attention i...

0 Jinshan Zeng, et al. ∙

research

∙ 10/16/2022

New Secure Sparse Inner Product with Applications to Machine Learning

Sparse inner product (SIP) has the attractive property of overhead being...

0 Guowen Xu, et al. ∙

research

∙ 10/16/2022

VerifyML: Obliviously Checking Model Fairness Resilient to Malicious Model Holder

In this paper, we present VerifyML, the first secure inference framework...

0 Guowen Xu, et al. ∙

research

∙ 08/07/2022

Adaptive Local Implicit Image Function for Arbitrary-scale Super-resolution

Image representation is critical for many visual tasks. Instead of repre...

0 Hongwei Li, et al. ∙

research

∙ 07/11/2022

SIMC 2.0: Improved Secure ML Inference Against Malicious Clients

In this paper, we study the problem of secure ML inference against a mal...

0 Guowen Xu, et al. ∙

research

∙ 07/11/2022

Hercules: Boosting the Performance of Privacy-preserving Federated Learning

In this paper, we address the problem of privacy-preserving federated ne...

0 Guowen Xu, et al. ∙

research

∙ 07/11/2022

Privacy-preserving Decentralized Deep Learning with Multiparty Homomorphic Encryption

Decentralized deep learning plays a key role in collaborative model trai...

0 Guowen Xu, et al. ∙

research

∙ 07/07/2022

What Makes for Automatic Reconstruction of Pulmonary Segments

3D reconstruction of pulmonary segments plays an important role in surgi...

14 Kaiming Kuang, et al. ∙

research

∙ 07/02/2022

Domain-Adaptive 3D Medical Image Synthesis: An Efficient Unsupervised Approach

Medical image synthesis has attracted increasing attention because it co...

0 Qingqiao Hu, et al. ∙

research

∙ 05/17/2022

blob loss: instance imbalance aware loss functions for semantic segmentation

Deep convolutional neural networks have proven to be remarkably effectiv...

16 Florian Kofler, et al. ∙

research

∙ 03/19/2022

Relationformer: A Unified Framework for Image-to-Graph Generation

A comprehensive representation of an image requires understanding object...

10 Suprosanna, et al. ∙

research

∙ 02/14/2022

CodeGen-Test: An Automatic Code Generation Model Integrating Program Test Information

Automatic code generation is to generate the program code according to t...

0 Maosheng Zhong, et al. ∙

research

∙ 09/13/2021

ComFeel: Productivity is a Matter of the Senses Too

Indoor environmental quality has been found to impact employees' product...

0 Marios Constantinides, et al. ∙

research

∙ 04/22/2021

METGAN: Generative Tumour Inpainting and Modality Synthesis in Light Sheet Microscopy

Novel multimodal imaging methods are capable of generating extensive, su...

7 Izabela Horvath, et al. ∙

research

∙ 03/10/2021

Are we using appropriate segmentation metrics? Identifying correlates of human expert perception for CNN training beyond rolling the DICE coefficient

In this study, we explore quantitative correlates of qualitative human e...

29 Florian Kofler, et al. ∙

research

∙ 03/06/2021

Imbalance-Aware Self-Supervised Learning for 3D Radiomic Representations

Radiomic representations can quantify properties of regions of interest ...

19 Hongwei Li, et al. ∙

research

∙ 01/05/2021

Deep Class-Specific Affinity-Guided Convolutional Network for Multimodal Unpaired Image Segmentation

Multi-modal medical image segmentation plays an essential role in clinic...

0 Jingkun Chen, et al. ∙

research

∙ 10/27/2020

Micro-CT Synthesis and Inner Ear Super Resolution via Bayesian Generative Adversarial Networks

Existing medical image super-resolution methods rely on pairs of low- an...

0 Hongwei Li, et al. ∙

research

∙ 08/08/2020

Complex Grey Matter Structure Segmentation in Brains via Deep Learning: Example of the Claustrum

Segmentationand parcellation of the brain has been widely performed on b...

46 Hongwei Li, et al. ∙

research

∙ 08/03/2020

Generalisable Cardiac Structure Segmentation via Attentional and Stacked Image Adaptation

Tackling domain shifts in multi-centre and multi-vendor data sets remain...

0 Hongwei Li, et al. ∙

research

∙ 04/22/2020

Red-GAN: Attacking class imbalance via conditioned generation. Yet another medical imaging perspective

Exploiting learning algorithms under scarce data regimes is a limitation...

8 Ahmad B Qasim, et al. ∙

research

∙ 01/25/2020

e-UDA: Efficient Unsupervised Domain Adaptation for Cross-Site Medical Image Segmentation

Domain adaptation in healthcare data is a potentially critical component...

17 Hongwei Li, et al. ∙

research

∙ 12/12/2019

Fast non-convex low-rank matrix decomposition for separation of potential field data using minimal memory

A fast non-convex low-rank matrix decomposition method for potential fie...

0 Dan Zhu, et al. ∙

research

∙ 09/21/2019

Invasiveness Prediction of Pulmonary Adenocarcinomas Using Deep Feature Fusion Networks

Early diagnosis of pathological invasiveness of pulmonary adenocarcinoma...

0 Xiang Li, et al. ∙

research

∙ 08/25/2019

Adversarial Convolutional Networks with Weak Domain-Transfer for Multi-Sequence Cardiac MR Images Segmentation

Analysis and modeling of the ventricles and myocardium are important in ...

21 Jingkun Chen, et al. ∙

research

∙ 08/05/2019

Restricted Linearized Augmented Lagrangian Method for Euler's Elastica Model

Euler's elastica model has been extensively studied and applied to image...

3 Yinghui Zhang, et al. ∙

research

∙ 07/01/2019

Cross-view Relation Networks for Mammogram Mass Detection

Mammogram is the most effective imaging modality for the mass lesion det...

0 Jiechao Ma, et al. ∙

research

∙ 04/29/2019

DiamondGAN: Unified Multi-Modal Generative Adversarial Networks for MRI Sequences Synthesis

Recent studies on medical image synthesis reported promising results usi...

0 Hongwei Li, et al. ∙

research

∙ 04/01/2019

Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities and Results of the WMH Segmentation Challenge

Quantification of cerebral white matter hyperintensities (WMH) of presum...

0 Hugo J. Kuijf, et al. ∙

research

∙ 12/18/2018

Group-Attention Single-Shot Detector (GA-SSD): Finding Pulmonary Nodules in Large-Scale CT Images

Early diagnosis of pulmonary nodules (PNs) can improve the survival rate...

0 Jiechao Ma, et al. ∙

research

∙ 11/10/2018

Automatic Brain Structures Segmentation Using Deep Residual Dilated U-Net

Brain image segmentation is used for visualizing and quantifying anatomi...

0 Hongwei Li, et al. ∙

research

∙ 11/05/2018

Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

Gliomas are the most common primary brain malignancies, with different d...

0 Spyridon Bakas, et al. ∙

research

∙ 10/22/2018

Hierarchical multi-class segmentation of glioma images using networks with multi-level activation function

For many segmentation tasks, especially for the biomedical image, the to...

0 Xiaobin Hu, et al. ∙

research

∙ 07/13/2018

Multi-Scale Convolutional-Stack Aggregation for Robust White Matter Hyperintensities Segmentation

Segmentation of both large and small white matter hyperintensities/lesio...

0 Hongwei Li, et al. ∙

research

∙ 06/04/2018

Differential Diagnosis for Pancreatic Cysts in CT Scans Using Densely-Connected Convolutional Networks

The lethal nature of pancreatic ductal adenocarcinoma (PDAC) calls for e...

0 Hongwei Li, et al. ∙

research

∙ 02/14/2018

Fully Convolutional Network Ensembles for White Matter Hyperintensities Segmentation in MR Images

White matter hyperintensities (WMH) are commonly found in the brains of ...

0 Hongwei Li, et al. ∙

research

∙ 02/03/2015

Cheaper and Better: Selecting Good Workers for Crowdsourcing

Crowdsourcing provides a popular paradigm for data collection at scale. ...

0 Hongwei Li, et al. ∙

research

∙ 11/15/2014

Error Rate Bounds and Iterative Weighted Majority Voting for Crowdsourcing

Crowdsourcing has become an effective and popular tool for human-powered...

0 Hongwei Li, et al. ∙

research

∙ 07/10/2013

Error Rate Bounds in Crowdsourcing Models

Crowdsourcing is an effective tool for human-powered computation on many...

0 Hongwei Li, et al. ∙

Hongwei Li

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