AN OBJECT PROPERTIES FILTER FOR MULTI-MODALITY ONTOLOGY SEMANTIC IMAGE RETRIEVAL
Journal of ICT, 2017 Ontology is a semantic technology that provides the possible approach to bridge the issue on semantic gap in image retrieval between low-level visual features and high-level human semantic.
Mohd Suffian Sulaiman +2 more
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Study on Cross-media Information Retrieval Based on Common Subspace Classification Learning [PDF]
Jisuanji kexue, 2022 The semantic similarity between two different media data can not be calculated directly because of the serious heterogeneous gap and semantic gap between them,which affects the implementation and effect of cross media retrieval.Although the common space ...
HAN Hong-qi, RAN Ya-xin, ZHANG Yun-liang, GUI Jie, GAO Xiong, YI Meng-lin
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Organizational challenges of the semantic web in digital libraries [PDF]
, 2008 The Semantic Web initiative holds large promises for the future. There is, however, a considerable gap in Semantic Web research between the contributions in the technological field and the research done in the organizational field.
Bygstad, B, Ghinea, G, Klaebo, GT
core +1 more source
DA-GAN: Dual Attention Generative Adversarial Network for Cross-Modal Retrieval
Future Internet, 2022 Cross-modal retrieval aims to search samples of one modality via queries of other modalities, which is a hot issue in the community of multimedia. However, two main challenges, i.e., heterogeneity gap and semantic interaction across different modalities,
Liewu Cai +3 more
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Cograph Regularized Collective Nonnegative Matrix Factorization for Multilabel Image Annotation
IEEE Access, 2019 Automatic image annotation is an effective and straightforward way to facilitate many applications in computer vision. However, manually annotating images is a computation-expensive and labor-intensive task. To address these problems, this paper proposes
Juli Zhang +3 more
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Understanding Heterogeneous EO Datasets: A Framework for Semantic Representations
IEEE Access, 2018 Earth observation (EO) has become a valuable source of comprehensive, reliable, and persistent information for a wide number of applications. However, dealing with the complexity of land cover is sometimes difficult, as the variety of EO sensors reflects
Corina Vaduva +2 more
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Multi-Modal Fake News Detection via Bridging the Gap between Modals
Entropy, 2023 Multi-modal fake news detection aims to identify fake information through text and corresponding images. The current methods purely combine images and text scenarios by a vanilla attention module but there exists a semantic gap between different ...
Peng Liu +4 more
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DGFNet: Dual Gate Fusion Network for Land Cover Classification in Very High-Resolution Images
Remote Sensing, 2021 Deep convolutional neural networks (DCNNs) have been used to achieve state-of-the-art performance on land cover classification thanks to their outstanding nonlinear feature extraction ability. DCNNs are usually designed as an encoder–decoder architecture
Yongjie Guo +3 more
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A Semantic Graph-Based Approach for Mining Common Topics From Multiple Asynchronous Text Streams [PDF]
, 2017 In the age of Web 2.0, a substantial amount of unstructured content are distributed through multiple text streams in an asynchronous fashion, which makes it increasingly difficult to glean and distill useful information.
Guo Weiwei +6 more
core +1 more source
Visual Description Augmented Integration Network for Multimodal Entity and Relation Extraction
Applied Sciences, 2023 Multimodal Named Entity Recognition (MNER) and multimodal Relationship Extraction (MRE) play an important role in processing multimodal data and understanding entity relationships across textual and visual domains.
Min Zuo +5 more
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