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Semantic-enhanced graph neural networks with global context representation
Node classification is a crucial task for efficiently analyzing graph-structured data. Related semi-supervised methods have been extensively studied...
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Multi-label image classification with multi-layered multi-perspective dynamic semantic representation
With the development of deep learning techniques, multi-label image classification tasks have achieved good performance. Recently, graph...
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PRCL: Probabilistic Representation Contrastive Learning for Semi-Supervised Semantic Segmentation
Tremendous breakthroughs have been developed in Semi-Supervised Semantic Segmentation (S4) through contrastive learning. However, due to limited...
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Multi-representation decoupled joint network for semantic segmentation of remote sensing images
In recent years, semantic segmentation has become an important means of processing remote sensing images, and it is widely used in various fields...
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Fake news detection: deep semantic representation with enhanced feature engineering
Due to the widespread use of social media, people are exposed to fake news and misinformation. Spreading fake news has adverse effects on both the...
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Dot-to-Dot Semantic Representation
This paper introduces dot-to-dot semantic representation as an encoding for abstract dependency interpretations of natural language data. The...
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FRSE-Net: low-illumination object detection network based on feature representation refinement and semantic-aware enhancement
Deep learning-based object detection methods have achieved great performance improvement. However, the current mainstream object detectors focus on...
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Exploring semantic awareness via graph representation for text classification
Text classification is a fundamental problem in natural language processing. Nowadays, text classification based on GNN attracts the attention of...
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Semantic-aware visual scene representation
Scene classification is a mature and active computer vision task, due to the inherent ambiguity. The scene classification task aims to classify the...
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Conception and Linguistic Means of Representation and Knowledge Processing at the Semantic Level
Abstract —The requirements that knowledge representation languages must meet are determined. It is concluded that the reasons for the failures of...
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A residual semantic graph convolutional network with high-resolution representation for 3D human pose estimation in a virtual fashion show
3D human pose estimation has achieved rapid progress in virtual fashion shows. Loose clothing and personalized poses in virtual fashion shows often...
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Joint semantic embedding with structural knowledge and entity description for knowledge representation learning
Previous works mainly employ triple structural information in learning representations for knowledge graph, which results in poor performance of link...
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A Prototype Network Enhanced Relation Semantic Representation for Few-shot Relation Extraction
Few-shot relation extraction is one of the current research focuses. The key to this research is to fully extract the relation semantic information...
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SubTST: a consolidation of sub-word latent topics and sentence transformer in semantic representation
In most applications, text understanding and representation always play an important role, especially in automatic processing. Together with the...
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Semantic representation of neural circuit knowledge in Caenorhabditis elegans
In modern biology, new knowledge is generated quickly, making it challenging for researchers to efficiently acquire and synthesise new information...
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Learning Semantic Representation for Binary Code Similarity Detection
To avoid the human bias introduced by numerical statistical features and overcome difficulty in cross platform and optimization detection methods,...
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Research on semantic representation and citation recommendation of scientific papers with multiple semantics fusion
With the growth in scientific papers, citation recommendation which enables researchers to find useful references efficiently and further to promote...
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Sfnet: Faster and Accurate Semantic Segmentation Via Semantic Flow
In this paper, we focus on exploring effective methods for faster and accurate semantic segmentation. A common practice to improve the performance is...
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Semantic-specific multimodal relation learning for sentiment analysis
Multimodal sentiment analysis (MSA) seeks to understand human affection by leveraging signals from multiple modalities. A core challenge in MSA is...
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Fuzzy Semantic Networks as a Knowledge Representation Model of Autonomous Intelligent Systems
Abstract—This paper considers the main characteristics of goal-oriented behavior displayed by autonomous intelligent systems in conditions of a...