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Found 4 papers, 1 papers with code
Deep Learning-Based Detection for Marker Codes over Insertion and Deletion Channels
In this paper, we propose two CSI-agnostic detecting algorithms for marker code based on deep learning.
Hierarchical Contrastive Learning Enhanced Heterogeneous Graph Neural Network
Specifically, two views of a HIN (network schema and meta-path views) are proposed to learn node embeddings, so as to capture both of local and high-order structures simultaneously.
Robust Implementation of Foreground Extraction and Vessel Segmentation for X-ray Coronary Angiography Image Sequence
Based on TV-TRPCA, the accuracy of TSRG algorithm for vessel segmentation is further evaluated.
Self-supervised Heterogeneous Graph Neural Network with Co-contrastive Learning
Then the cross-view contrastive learning, as well as a view mask mechanism, is proposed, which is able to extract the positive and negative embeddings from two views.
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