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Enhancing knowledge graph embedding with structure and semantic features
Knowledge graph embedding converts knowledge graphs based on symbolic representations into low-dimensional vectors. Effective knowledge graph...
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Real-World Semantic Grasp Detection Using Ontology Features: Learning to Concentrate on Object Features
Recognizing the category of the object and using the features of the object itself to predict grasp configuration is of great significance to improve...
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Retrieving images with missing regions by fusion of content and semantic features
Deep neural networks with a significant ability to learn and extract image discriminative features make a significant contribution to image retrieval...
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EnCoSum: enhanced semantic features for multi-scale multi-modal source code summarization
Code summarization aims to generate concise natural language descriptions for a piece of code, which can help developers comprehend the source code....
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Semantic features analysis for biomedical lexical answer type prediction using ensemble learning approach
Lexical answer type prediction is integral to biomedical question–answering systems. LAT prediction aims to predict the expected answer’s semantic...
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Extraction and Analysis of Semantic Features of English Texts under Intelligent Algorithms
AbstractAccurate identification and analysis of semantics is beneficial for processing English texts effectively. This article briefly introduced...
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Classification of aesthetic natural scene images using statistical and semantic features
Aesthetic image analysis is essential for improving the performance of multimedia image retrieval systems, especially from a repository of social...
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Exploring the research features of Nobel laureates in Physics based on the semantic similarity measurement
Exploring the temporal research features of Nobel laureates’ papers based on the semantic measurement indexes is helpful to understand the successful...
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Learning local contextual features for 3D point clouds semantic segmentation by attentive kernel convolution
Unlike 2D images that are represented in regular grids, 3D point clouds are irregular and unordered, hence directly applying convolution neural...
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Log Anomaly Detection Based on Semantic Features and Topic Features
System logs serve as crucial data sources for monitoring system performance and enhancing service quality. Many existing log-based anomaly detection...
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ZMNet: feature fusion and semantic boundary supervision for real-time semantic segmentation
Feature fusion module is an essential component of real-time semantic segmentation networks to bridge the semantic gap among different feature...
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CLINER: exploring task-relevant features and label semantic for few-shot named entity recognition
Few-shot named entity recognition aims at recognizing novel-class named entities in low resources scenarios. Low resource scenarios contain limited...
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Unsupervised tweets categorization using semantic and statistical features
Clustering is one of the widely used techniques in information retrieval. This experiment intends to categorize Tweets (based on their content) as...
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Poetic and Semantic Features for Lyricist Identification from Tamil Film Lyrics
Authorship attribution has been largely investigated based on writing style analysis to identify the author of a given document. This paper describes...
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Matching Visual Features to Hierarchical Semantic Topics for Image Paragraph Captioning
Observing a set of images and their corresponding paragraph-captions, a challenging task is to learn how to produce a semantically coherent paragraph...
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Automated Essay Scoring Incorporating Multi-level Semantic Features
Essay writing might reveal the language proficiency of a student. Utilizing intelligent technology to automatically grade essays is an effective...
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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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Two-Stage Knowledge Graph Completion Based on Semantic Features and High-Order Structural Features
Recently, multi-head Graph Attention Networks (GATs) have incorporated attention mechanisms to generate more enriched feature embeddings,...
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Position attention optimized deep semantic segmentation
Semantic segmentation can be applied in various fields of computer vision such as scene understanding. In order to assist intelligent machines to...
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Zero-shot image classification via Visual–Semantic Feature Decoupling
Zero-shot image classification refers to the use of labeled images to train a classification model that can correctly classify images of unseen...
