Article-Journal

Semi-supervised learning for multi-view and non-graph data using Graph Convolutional Networks
Semi-supervised learning with a graph-based approach has become increasingly popular in machine learning, particularly when dealing …
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The role of artificial intelligence in implant dentistry: a systematic review
The aim of this systematic review was to comprehensively analyse recent studies on the application of artificial intelligence (AI) in …
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Unified multi-view data clustering: Simultaneous learning of consensus coefficient matrix and similarity graph
Integrating data from multiple sources or views has become increasingly common in data analysis, particularly in fields like …
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An End-to-End Approach for Graph-Based Multi-View Data Clustering
Clustering data from different sources or views is a key challenge in real-world applications. While traditional graph-based methods …
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Scalable and Inductive Semi-supervised Classifier with Sample Weighting Based on Graph Topology
Recently, graph-based semi-supervised learning (GSSL) has garnered significant interest in the realms of machine learning and pattern …
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A deep learning method that identifies cellular heterogeneity using nanoscale nuclear features
Cellular phenotypic heterogeneity is an important hallmark of many biological processes and understanding its origins remains a …
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Automatic mapping of aquaculture activity in the Atlantic Ocean
The production of wild fish has remained relatively stable in the last two decades, whereas aquaculture organism production has …
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Clustering using graph convolution networks
Graph convolution networks (GCNs) have emerged as powerful approaches for semi-supervised classification of attributed graph data. In …
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Data augmentation for deep visual recognition using superpixel based pairwise image fusion
Data augmentation is an important paradigm for boosting the generalization capability of deep learning in image classification tasks. …
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Discriminative Feature Learning Through Angular Margin-Based Softmax Losses for Breast Cancer Classification
When many histopathological breast images with different magnification levels need to be analyzed, diagnosing benign or malignant …
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