Liangrui Pan
Orcid: 0000-0003-0565-4217
According to our database1,
Liangrui Pan
authored at least 29 papers
between 2020 and 2024.
Collaborative distances:
Collaborative distances:
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Bibliography
2024
Optimization of the parallel semi-Lagrangian scheme to overlap computation with communication based on grouping levels in YHGSM.
CCF Trans. High Perform. Comput., February, 2024
Feature-interactive Siamese graph encoder-based image analysis to predict STAS from histopathology images in lung cancer.
CoRR, 2024
FedDP: Privacy-preserving method based on federated learning for histopathology image segmentation.
CoRR, 2024
FORESEE: Multimodal and Multi-view Representation Learning for Robust Prediction of Cancer Survival.
CoRR, 2024
Opportunities and challenges in the application of large artificial intelligence models in radiology.
CoRR, 2024
DEDUCE: Multi-head attention decoupled contrastive learning to discover cancer subtypes based on multi-omics data.
Comput. Methods Programs Biomed., 2024
SELECTOR: Heterogeneous graph network with convolutional masked autoencoder for multimodal robust prediction of cancer survival.
Comput. Biol. Medicine, 2024
2023
DHUnet: Dual-branch hierarchical global-local fusion network for whole slide image segmentation.
Biomed. Signal Process. Control., August, 2023
Palm bunch grading technique using a multi-input and multi-label convolutional neural network.
Comput. Electron. Agric., July, 2023
PACS: Prediction and analysis of cancer subtypes from multi-omics data based on a multi-head attention mechanism model.
CoRR, 2023
CVFC: Attention-Based Cross-View Feature Consistency for Weakly Supervised Semantic Segmentation of Pathology Images.
CoRR, 2023
LDCSF: Local depth convolution-based Swim framework for classifying multi-label histopathology images.
CoRR, 2023
Multi-Head Attention Mechanism Learning for Cancer New Subtypes and Treatment Based on Cancer Multi-Omics Data.
CoRR, 2023
PACS: Prediction and analysis of cancer subtypes from multi-omics data based on a multi-head attention mechanism model.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023
CVFC: Attention-Based Cross-View Feature Consistency for Weakly Supervised Semantic Segmentation of Pathology Images.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023
LDCSF: Local depth convolution-based Swim framework for classifying multi-label histopathology images.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023
2022
Hybrid Beamforming Based on an Unsupervised Deep Learning Network for Downlink Channels With Imperfect CSI.
IEEE Wirel. Commun. Lett., 2022
MFDNN: multi-channel feature deep neural network algorithm to identify COVID19 chest X-ray images.
Health Inf. Sci. Syst., 2022
CoRR, 2022
A review of machine learning approaches, challenges and prospects for computational tumor pathology.
CoRR, 2022
Noise-reducing attention cross fusion learning transformer for histological image classification of osteosarcoma.
Biomed. Signal Process. Control., 2022
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022
2021
A review of artificial intelligence methods combined with Raman spectroscopy to identify the composition of substances.
CoRR, 2021
FEDI: Few-shot learning based on Earth Mover's Distance algorithm combined with deep residual network to identify diabetic retinopathy.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021
DFL-PiDA: Prediction of Piwi-interacting RNA-Disease Associations based on Deep Feature Learning.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021
2020
Identification of complex mixtures for Raman spectroscopy using a novel scheme based on a new multi-label deep neural network.
CoRR, 2020
Method for Classifying a Noisy Raman Spectrum Based on a Wavelet Transform and a Deep Neural Network.
IEEE Access, 2020
Proceedings of the 13th International Symposium on Computational Intelligence and Design, 2020
Classification of Hazardous Chemicals with Raman Spectrum by Convolution Neural Network.
Proceedings of the 13th International Conference on Human System Interaction, 2020