Search Results for author: Peijie Qiu

Found 13 papers, 9 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

AgileFormer: Spatially Agile Transformer UNet for Medical Image Segmentation

1 code implementation29 Mar 2024 Peijie Qiu, Jin Yang, Sayantan Kumar, Soumyendu Sekhar Ghosh, Aristeidis Sotiras

However, we argue that the current design of the vision transformer-based UNet (ViT-UNet) segmentation models may not effectively handle the heterogeneous appearance (e. g., varying shapes and sizes) of objects of interest in medical image segmentation tasks.

Image Segmentation Medical Image Segmentation +2

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

NSOTree: Neural Survival Oblique Tree

1 code implementation25 Sep 2023 Xiaotong Sun, Peijie Qiu

In this paper, we leverage the strengths of both neural networks and tree-based methods, capitalizing on their ability to approximate intricate functions while maintaining interpretability.

Survival Analysis

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

SC-VAE: Sparse Coding-based Variational Autoencoder with Learned ISTA

no code implementations29 Mar 2023 Pan Xiao, Peijie Qiu, Sungmin Ha, Abdalla Bani, Shuang Zhou, Aristeidis Sotiras

Several variants of variational autoencoders (VAEs) have been proposed to learn compact data representations by encoding high-dimensional data in a lower dimensional space.

Image Generation Image Reconstruction +5

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

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