Search Results for author: Wenhui Zhu

Found 14 papers, 6 papers with code

TimeMIL: Advancing Multivariate Time Series Classification via a Time-aware Multiple Instance Learning

1 code implementation6 May 2024 Xiwen Chen, Peijie Qiu, Wenhui Zhu, Huayu Li, Hao Wang, Aristeidis Sotiras, Yalin Wang, Abolfazl Razi

Deep neural networks, including transformers and convolutional neural networks, have significantly improved multivariate time series classification (MTSC).

Multiple Instance Learning Time Series +1

Imaging Signal Recovery Using Neural Network Priors Under Uncertain Forward Model Parameters

no code implementations5 May 2024 Xiwen Chen, Wenhui Zhu, Peijie Qiu, Abolfazl Razi

We theoretically demonstrate the convergence of the MA framework, which has a similar complexity with reconstruction under the known forward model parameters.

Compressive Sensing

Reconstructing Retinal Visual Images from 3T fMRI Data Enhanced by Unsupervised Learning

no code implementations7 Apr 2024 Yujian Xiong, Wenhui Zhu, Zhong-Lin Lu, Yalin Wang

The reconstruction of human visual inputs from brain activity, particularly through functional Magnetic Resonance Imaging (fMRI), holds promising avenues for unraveling the mechanisms of the human visual system.

Generative Adversarial Network

SC-MIL: Sparsely Coded Multiple Instance Learning for Whole Slide Image Classification

1 code implementation31 Oct 2023 Peijie Qiu, Pan Xiao, Wenhui Zhu, Yalin Wang, Aristeidis Sotiras

In this paper, we proposed a sparsely coded MIL (SC-MIL) that addresses those two aspects at the same time by leveraging sparse dictionary learning.

Dictionary Learning Image Classification +1

PDL: Regularizing Multiple Instance Learning with Progressive Dropout Layers

1 code implementation19 Aug 2023 Wenhui Zhu, Peijie Qiu, Xiwen Chen, Oana M. Dumitrascu, Yalin Wang

Multiple instance learning (MIL) was a weakly supervised learning approach that sought to assign binary class labels to collections of instances known as bags.

Multiple Instance Learning Weakly Supervised Classification +3

nnMobileNet: Rethinking CNN for Retinopathy Research

2 code implementations2 Jun 2023 Wenhui Zhu, Peijie Qiu, Xiwen Chen, Xin Li, Natasha Lepore, Oana M. Dumitrascu, Yalin Wang

Over the past few decades, convolutional neural networks (CNNs) have been at the forefront of the detection and tracking of various retinal diseases (RD).

Diabetic Retinopathy Grading

A Surface-Based Federated Chow Test Model for Integrating APOE Status, Tau Deposition Measure, and Hippocampal Surface Morphometry

no code implementations31 Mar 2023 Jianfeng Wu, Yi Su, Yanxi Chen, Wenhui Zhu, Eric M. Reiman, Richard J. Caselli, Kewei Chen, Paul M. Thompson, Junwen Wang, Yalin Wang

Objective: To build a surface-based model to 1) detect differences between APOE subgroups in patterns of tau deposition and hippocampal atrophy, and 2) use the extracted surface-based features to predict cognitive decline.

TetCNN: Convolutional Neural Networks on Tetrahedral Meshes

no code implementations8 Feb 2023 Mohammad Farazi, Zhangsihao Yang, Wenhui Zhu, Peijie Qiu, Yalin Wang

Our results show the superiority of our LBO-based convolution layer and adapted pooling over the conventionally used unitary cortical thickness, graph Laplacian, and point cloud representation.

OTRE: Where Optimal Transport Guided Unpaired Image-to-Image Translation Meets Regularization by Enhancing

2 code implementations6 Feb 2023 Wenhui Zhu, Peijie Qiu, Oana M. Dumitrascu, Jacob M. Sobczak, Mohammad Farazi, Zhangsihao Yang, Keshav Nandakumar, Yalin Wang

Non-mydriatic retinal color fundus photography (CFP) is widely available due to the advantage of not requiring pupillary dilation, however, is prone to poor quality due to operators, systemic imperfections, or patient-related causes.

Denoising Diabetic Retinopathy Grading +5

Improved Prediction of Beta-Amyloid and Tau Burden Using Hippocampal Surface Multivariate Morphometry Statistics and Sparse Coding

no code implementations28 Oct 2022 Jianfeng Wu, Yi Su, Wenhui Zhu, Negar Jalili Mallak, Natasha Lepore, Eric M. Reiman, Richard J. Caselli, Paul M. Thompson, Kewei Chen, Yalin Wang

Experimental results suggest that amyloid/tau measurements predicted with our PASCP-MP representations are closer to the real values than the measures derived from other approaches, such as hippocampal surface area, volume, and shape morphometry features based on spherical harmonics (SPHARM).

Anisotropic Multi-Scale Graph Convolutional Network for Dense Shape Correspondence

no code implementations17 Oct 2022 Mohammad Farazi, Wenhui Zhu, Zhangsihao Yang, Yalin Wang

This paper studies 3D dense shape correspondence, a key shape analysis application in computer vision and graphics.

3D Dense Shape Correspondence

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