Chengyun Song
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View article: Sc-Bsn: Shifted Convolutions Based Blind-Spot Network for Self-Supervised Image Denoising
Sc-Bsn: Shifted Convolutions Based Blind-Spot Network for Self-Supervised Image Denoising Open
View article: Stochastic Augmented-Based Dual-Teaching for Semi-Supervised Medical Image Segmentation
Stochastic Augmented-Based Dual-Teaching for Semi-Supervised Medical Image Segmentation Open
View article: Regularized deep learning for unsupervised random noise attenuation in poststack seismic data
Regularized deep learning for unsupervised random noise attenuation in poststack seismic data Open
Deep learning methods achieve excellent noise reduction performances in seismic data processing compared with traditional methods. However, deep learning usually requires a large number of pairwise noisy-clean training data, which is an ex…
View article: Robust K-means algorithm with weighted window for seismic facies analysis
Robust K-means algorithm with weighted window for seismic facies analysis Open
Seismic facies analysis can generate a map to describe the spatial distribution characteristics of reservoirs, and therefore plays a critical role in seismic interpretation. To analyse the characteristics of the horizon of interest, it is …
View article: A review of recommendation system research based on bipartite graph
A review of recommendation system research based on bipartite graph Open
The interaction history between users and items is usually stored and displayed in the form of bipartite graphs. Neural network recommendation based on the user-item bipartite graph has a significant effect on alleviating the long-standing…
View article: User abnormal behavior recommendation via multilayer network
User abnormal behavior recommendation via multilayer network Open
With the growing popularity of online services such as online banking and online shopping, one of the essential research topics is how to build a privacy-preserving user abnormal behavior recommendation system. However, a machine-learning …
View article: hpGAT: High-Order Proximity Informed Graph Attention Network
hpGAT: High-Order Proximity Informed Graph Attention Network Open
Graph neural networks (GNNs) have recently made remarkable breakthroughs in the paradigm of learning with graph-structured data. However, most existing GNNs limit the receptive field of the node on each layer to its connected (one-hop) nei…
View article: Unsupervised seismic facies analysis with spatial constraints using regularized fuzzy c-means
Unsupervised seismic facies analysis with spatial constraints using regularized fuzzy c-means Open
Seismic facies analysis techniques combine classification algorithms and seismic attributes to generate a map that describes main reservoir heterogeneities. However, most of the current classification algorithms only view the seismic attri…