Knowledge 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 ...

Colour 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 ...

Session-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 ...

Recently, 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 ...

• 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.
• ...

Recently, 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 ...

Dynamic 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 ...

• 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-...

Personalized 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 ...

Recently, 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 ...

As 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 ...

Accurate 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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• 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 ...

Multi-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 ...

• 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 ...

The 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 ...

Few-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 ...

High 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,...

Due 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 ...

This 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 ...

Due 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 ...

The 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 ...