Search Results for author: Liwen Xu

Found 8 papers, 2 papers with code

SELECTOR: Heterogeneous graph network with convolutional masked autoencoder for multimodal robust prediction of cancer survival

1 code implementation14 Mar 2024 Liangrui Pan, Yijun Peng, Yan Li, Xiang Wang, Wenjuan Liu, Liwen Xu, Qingchun Liang, Shaoliang Peng

To mitigate the impact of missing features within the modality on prediction accuracy, we devised a convolutional masked autoencoder (CMAE) to process the heterogeneous graph post-feature reconstruction.

Survival Prediction

CVFC: Attention-Based Cross-View Feature Consistency for Weakly Supervised Semantic Segmentation of Pathology Images

no code implementations21 Aug 2023 Liangrui Pan, Lian Wang, Zhichao Feng, Liwen Xu, Shaoliang Peng

Specifically, CVFC is a three-branch joint framework composed of two Resnet38 and one Resnet50, and the independent branch multi-scale integrated feature map to generate a class activation map (CAM); in each branch, through down-sampling and The expansion method adjusts the size of the CAM; the middle branch projects the feature matrix to the query and key feature spaces, and generates a feature space perception matrix through the connection layer and inner product to adjust and refine the CAM of each branch; finally, through the feature consistency loss and feature cross loss to optimize the parameters of CVFC in co-training mode.

Image Segmentation Segmentation +2

LDCSF: Local depth convolution-based Swim framework for classifying multi-label histopathology images

no code implementations21 Aug 2023 Liangrui Pan, Yutao Dou, Zhichao Feng, Liwen Xu, Shaoliang Peng

In order to be able to provide local field of view diagnostic results, we propose the LDCSF model, which consists of a Swin transformer module, a local depth convolution (LDC) module, a feature reconstruction (FR) module, and a ResNet module.

Classification Image Classification

DEDUCE: Multi-head attention decoupled contrastive learning to discover cancer subtypes based on multi-omics data

1 code implementation9 Jul 2023 Liangrui Pan, Dazhen Liu, Yutao Dou, Lian Wang, Zhichao Feng, Pengfei Rong, Liwen Xu, Shaoliang Peng

In this study, we proposed a generalization framework based on attention mechanisms for unsupervised contrastive learning to analyze cancer multi-omics data for the identification and characterization of cancer subtypes.

Contrastive Learning

MGTUNet: An new UNet for colon nuclei instance segmentation and quantification

no code implementations20 Oct 2022 Liangrui Pan, Lian Wang, Zhichao Feng, Zhujun Xu, Liwen Xu, Shaoliang Peng

Cellular nuclei instance segmentation and classification, and nuclear component regression tasks can aid in the analysis of the tumor microenvironment in colon tissue.

Instance Segmentation regression +2

MDAN: Multi-level Dependent Attention Network for Visual Emotion Analysis

no code implementations CVPR 2022 Liwen Xu, Zhengtao Wang, Bin Wu, Simon Lui

Existing deep approaches try to bridge the gap by directly learning discrimination among emotions globally in one shot without considering the hierarchical relationship among emotions at different affective levels and the affective level of emotions to be classified.

Emotion Recognition

Soft-Median Choice: An Automatic Feature Smoothing Method for Sound Event Detection

no code implementations25 Nov 2020 Fengnian Zhao, Ruwei Li, Xin Liu, Liwen Xu

In Sound Event Detection (SED) systems, the lengths of median filters for post-processing have never been optimized during training due to several problems.

Event Detection Sound Event Detection

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