Search Results for author:
Found 10 papers, 1 papers with code
ChicHealth @ MEDIQA 2021: Exploring the limits of pre-trained seq2seq models for medical summarization
In this article, we will describe our system for MEDIQA2021 shared tasks.
Fixed-time Disturbance Observer-Based MPC Robust Trajectory Tracking Control of Quadrotor
In this paper, a fixed-time disturbance observerbased model predictive control algorithm is proposed for trajectory tracking of quadrotor in the presence of disturbances.
FORESEE: Multimodal and Multi-view Representation Learning for Robust Prediction of Cancer Survival
Integrating the different data modalities of cancer patients can significantly improve the predictive performance of patient survival.
SELECTOR: Heterogeneous graph network with convolutional masked autoencoder for multimodal robust prediction of cancer survival
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.
CVFC: Attention-Based Cross-View Feature Consistency for Weakly Supervised Semantic Segmentation of Pathology Images
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.
LDCSF: Local depth convolution-based Swim framework for classifying multi-label histopathology images
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.
DEDUCE: Multi-head attention decoupled contrastive learning to discover cancer subtypes based on multi-omics data
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.
MGTUNet: An new UNet for colon nuclei instance segmentation and quantification
Cellular nuclei instance segmentation and classification, and nuclear component regression tasks can aid in the analysis of the tumor microenvironment in colon tissue.
MDAN: Multi-level Dependent Attention Network for Visual Emotion Analysis
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.
Soft-Median Choice: An Automatic Feature Smoothing Method for Sound Event Detection
In Sound Event Detection (SED) systems, the lengths of median filters for post-processing have never been optimized during training due to several problems.
