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- ArticleSeptember 2024
Graph Attention Network with Relational Dynamic Factual Fusion for Knowledge Graph Completion
Machine Learning and Knowledge Discovery in Databases. Research TrackPages 89–106https://doi.org/10.1007/978-3-031-70359-1_6AbstractKnowledge graph completion (KGC) completes knowledge graphs integrity by predicting missing entities in triples. Existing KGC models have achieved excellent results, especially graph attention network models (GATs). Existing GATs ignore the ...
- research-articleOctober 2024
Vision graph convolutional network for underwater image enhancement
AbstractColour deviation, non-uniform degradation, and decreased contrast often occur in underwater images because a certain amount of light is absorbed and dispersed underwater. To address this problem, a graph convolution-based underwater image ...
- ArticleAugust 2024
Global Context Enhanced Multi-granularity Intent Networks for Session-Based Recommendation
Knowledge Science, Engineering and ManagementPages 375–386https://doi.org/10.1007/978-981-97-5501-1_28AbstractSession-Based Recommendation (SBR) aims to recommend the next item based on short sets of anonymous user’s behaviors. Due to the lack of user profiles, item transition information plays an important role in capturing user intent. Advancements in ...
- review-articleSeptember 2024
Hierarchical slice interaction and multi-layer cooperative decoding networks for remote sensing image dehazing
AbstractRecently, U-shaped neural networks have gained widespread application in remote sensing image dehazing and achieved promising performance. However, most of the existing U-shaped dehazing networks neglect the global and local information ...
Highlights- We propose a method (HSMD-Net) for haze removal in remote sensing images.
- A new reconstruction module and a new information interaction module.
- The method can produce reliable results under various concentrations of haze.
- ...
- research-articleAugust 2024
Unsupervised Bidirectional Contrastive Reconstruction and Adaptive Fine-Grained Channel Attention Networks for image dehazing
AbstractRecently, Unsupervised algorithms has achieved remarkable performance in image dehazing. However, the CycleGAN framework can lead to confusion in generator learning due to inconsistent data distributions, and the DisentGAN framework lacks ...
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- research-articleJuly 2024
Cracks-suppression perceptual geometry coding for dynamic point clouds
AbstractDynamic point clouds can effectively describe 3D objects and natural scenes, providing users with an immersive visual experience, but their huge amount of data requires efficient compression tools. To this end, the video-based point cloud ...
- research-articleJuly 2024
HDR light field imaging of dynamic scenes: A learning-based method and a benchmark dataset
Highlights- A novel learning-based method is proposed for ghost-free high dynamic range (HDR) light field imaging.
- A multi-scale architecture integrating deformable alignment module and angular embedding module is designed.
- A new large-scale ...
Light field (LF) imaging is an effective way to enable immersive applications. However, limited by the potential well capacity of the image sensor, the acquired LF images suffer from low dynamic range and are thus prone to under-exposure or over-...
- research-articleJune 2024
A Causal View for Multi-Interest User Modeling in News Recommendation
ICMR '24: Proceedings of the 2024 International Conference on Multimedia RetrievalPages 433–441https://doi.org/10.1145/3652583.3658093Personalized news recommendations are challenging due to the huge number of daily articles. While deep learning has achieved success in news recommendations, methods in the past often overlook the diversity of users' preferences. Recent works have ...
- ArticleMay 2024
Two-Stage Knowledge Graph Completion Based on Semantic Features and High-Order Structural Features
Advances in Knowledge Discovery and Data MiningPages 143–155https://doi.org/10.1007/978-981-97-2242-6_12AbstractRecently, multi-head Graph Attention Networks (GATs) have incorporated attention mechanisms to generate more enriched feature embeddings, demonstrating significant potential in Knowledge Graph Completion (KGC) tasks. However, existing GATs based ...
- research-articleSeptember 2024
A Green Electricity Certificate Scheme Based on Blockchain
FAIML '24: Proceedings of the 2024 3rd International Conference on Frontiers of Artificial Intelligence and Machine LearningPages 361–364https://doi.org/10.1145/3653644.3665217As the demand for renewable energy continues to grow, the transparency and credibility of green power certificate transactions have become extremely important. In this paper, an innovative solution is proposed to address the current authentication and ...
- research-articleJuly 2024
Local and Long-range Convolutional LSTM Network: A novel multi-step wind speed prediction approach for modeling local and long-range spatial correlations based on ConvLSTM
Engineering Applications of Artificial Intelligence (EAAI), Volume 130, Issue Chttps://doi.org/10.1016/j.engappai.2023.107613AbstractAccurate wind speed prediction is crucial for enhancing the stability and economic efficiency of power system operation, particularly in wind power grid integration. However, existing methods face challenges as they fail to explicitly model local ...
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Highlights- This study integrates local and long-range spatial correlations in wind speed prediction.
- Residual Deformable Convolution Module is utilized to capture local spatial correlations of wind speed flows outstandingly.
- Dense Coordinate ...
- research-articleMarch 2024
Global Heterogeneous Graph and Target Interest Denoising for Multi-behavior Sequential Recommendation
WSDM '24: Proceedings of the 17th ACM International Conference on Web Search and Data MiningPages 387–395https://doi.org/10.1145/3616855.3635857Multi-behavior sequential recommendation (MBSR) predicts a user's next item of interest based on their interaction history across different behavior types. Although existing studies have proposed capturing the correlation between different types of ...
- research-articleMarch 2024
Learning zero-shot dense light field reconstruction from heterogeneous imaging
Highlights- A zero-shot learning method is developed to reconstruct densely-sampled light fields.
- A cycle consistency constraint is designed to explore the characteristics of heterogeneous imaging.
- A simple and effective scheme is proposed to ...
Due to the limited sensor size, light field (LF) imaging usually suffers from an essential trade-off between its spatial and angular resolutions. Recently, some approaches have been proposed to use hybrid lens imaging to enhance spatial ...
- research-articleJanuary 2024
Learning Neighbor User Intention on User–Item Interaction Graphs for Better Sequential Recommendation
ACM Transactions on the Web (TWEB), Volume 18, Issue 2Article No.: 21, Pages 1–28https://doi.org/10.1145/3580520The task of sequential recommendation aims to predict a user’s preference by analyzing the user’s historical behaviours. Existing methods model item transitions through leveraging sequential patterns. However, they mainly consider the target user’s ...
- research-articleDecember 2023
CLINER: exploring task-relevant features and label semantic for few-shot named entity recognition
Neural Computing and Applications (NCAA), Volume 36, Issue 9Pages 4679–4691https://doi.org/10.1007/s00521-023-09285-3AbstractFew-shot named entity recognition aims at recognizing novel-class named entities in low resources scenarios. Low resource scenarios contain limited data in the support set with sparse labels. Existing methods neglect the relevance of the support ...
- research-articleFebruary 2024
Visual Quality Assessment of HDR Omnidirectional Image System Based on Viewport Feature Learning
ICAIP '23: Proceedings of the 2023 7th International Conference on Advances in Image ProcessingPages 64–69https://doi.org/10.1145/3635118.3635127High dynamic range (HDR) omnidirectional image system can provide users with an immersive visual experience, but its coding, transmission and visualization processes will cause corresponding coding distortion, tone mapping distortion and mixed distortion,...
- research-articleFebruary 2024
Single-image HDR Reconstruction based on Mask-aware Convolution
ICAIP '23: Proceedings of the 2023 7th International Conference on Advances in Image ProcessingPages 22–27https://doi.org/10.1145/3635118.3635122Due to the hardware limitations of the sensor during camera shooting, there is loss of details in underexposed and overexposed regions of an image. Inverse tone mapping is an effective approach to extend the dynamic range of the image. To correctly ...
- research-articleNovember 2023
Mean field games of energy storage devices: A finite difference analysis
AbstractThis paper considers a mean field game of energy storage devices (ESDs) in power systems, where electrovalency is affected by the storage population. The competition processes of ESDs are characterized by a pair of coupled partial differential ...
- research-articleNovember 2023
Stitched Wide Field of View Light Field Image Quality Assessment: Benchmark Database and Objective Metric
IEEE Transactions on Multimedia (TOM), Volume 26Pages 5092–5107https://doi.org/10.1109/TMM.2023.3330096Due to the limitation of commercial light field camera hardware devices, the imaging field of view is quite narrow. Numerous Light Field Image (LFI) stitching algorithms have been developed to expand the field of view. However, it is highly challenging to ...
- research-articleOctober 2023
Underwater Image Quality Assessment from Synthetic to Real-world: Dataset and Objective Method
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), Volume 20, Issue 3Article No.: 71, Pages 1–23https://doi.org/10.1145/3624983The complicated underwater environment and lighting conditions lead to severe influence on the quality of underwater imaging, which tends to impair underwater exploration and research. To effectively evaluate the quality of underwater images, an ...