Search Results for author: Xuanyu Zhu

Found 6 papers, 5 papers with code

HIRL: A General Framework for Hierarchical Image Representation Learning

1 code implementation26 May 2022 Minghao Xu, Yuanfan Guo, Xuanyu Zhu, Jiawen Li, Zhenbang Sun, Jian Tang, Yi Xu, Bingbing Ni

This framework aims to learn multiple semantic representations for each image, and these representations are structured to encode image semantics from fine-grained to coarse-grained.

Image Clustering Representation Learning +3

BFRnet: A deep learning-based MR background field removal method for QSM of the brain containing significant pathological susceptibility sources

1 code implementation6 Apr 2022 Xuanyu Zhu, Yang Gao, Feng Liu, Stuart Crozier, Hongfu Sun

The BFRnet method is compared with three conventional BFR methods and one previous deep learning method using simulated and in vivo brains from 4 healthy and 2 hemorrhagic subjects.

HCSC: Hierarchical Contrastive Selective Coding

2 code implementations CVPR 2022 Yuanfan Guo, Minghao Xu, Jiawen Li, Bingbing Ni, Xuanyu Zhu, Zhenbang Sun, Yi Xu

In this framework, a set of hierarchical prototypes are constructed and also dynamically updated to represent the hierarchical semantic structures underlying the data in the latent space.

Contrastive Learning Representation Learning

Deep grey matter quantitative susceptibility mapping from small spatial coverages using deep learning

no code implementations1 Jun 2021 Xuanyu Zhu, Yang Gao, Feng Liu, Stuart Crozier, Hongfu Sun

Method: A recently proposed deep learning-based QSM method, namely xQSM, is investigated to assess the accuracy of dipole inversion on reduced brain coverages.

xQSM-Quantitative Susceptibility Mapping with Octave Convolutional Neural Networks

1 code implementation14 Apr 2020 Yang Gao, Xuanyu Zhu, Stuart Crozier, Feng Liu, Hongfu Sun

Quantitative susceptibility mapping (QSM) is a valuable magnetic resonance imaging (MRI) contrast mechanism that has demonstrated broad clinical applications.

Image and Video Processing

Quaternion Convolutional Neural Networks

1 code implementation ECCV 2018 Xuanyu Zhu, Yi Xu, Hongteng Xu, Changjian Chen

Neural networks in the real domain have been studied for a long time and achieved promising results in many vision tasks for recent years.

Denoising Image Classification

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