Advancements in Earth observation technologies have greatly enhanced the potential of integrating hyperspectral (HS) images with Light Detection and Ranging (LiDAR) data for land use and land cover classification. Despite this, most existing ...

• A newly Cross-modal feature aggregation is introduced for HS and LiDAR.
• Two feature aggregation strategies refine spatial location details.
• INNs feature enhancement is to preserve local contextual integrity.

This paper presents quadrature rules for the space of functions underlying triangular Gregory patches, also called Gregory triangles. We provide numerical and where available symbolic quadrature rules not only for the space spanned by the fifteen ...

Cross-Domain Recommendation (CDR) has been proposed to improve the recommendation accuracy in the target domain (the sparser dataset) by benefiting from the auxiliary information transferred or the knowledge learned from one or many source domains (the ...

Accurate workload forecasting is critical for efficient resource management in cloud computing systems, enabling effective scheduling and autoscaling. Despite recent advances with transformer-based forecasting models, challenges remain due to the non-...

Temporal Knowledge Graph (TKG) reasoning is a crucial task that aims to predict future facts based on historical information. In the process of reasoning over TKGs, we identify two types of facts that need to be predicted: 1) recurring facts and 2) ...

Covariance matrix estimation is an important problem in statistics, with wide applications in finance, neuroscience, meteorology, oceanography, and other fields. However, when the data are high-dimensional and constantly generated and updated in a ...

Recently, the item textual information has been exploited with pre-trained language models (PLMs) to enrich the representations of tail items. The underlying idea is to align the hot items and tail items in terms of the external semantic knowledge ...

Recently, Large Language Models (LLMs) have shown significant potential in addressing the isolation issues faced by recommender systems. However, despite performance comparable to traditional recommenders, the current methods are cost-prohibitive for ...

Real-time fusion of intraoperative 2D ultrasound images and the preoperative 3D ultrasound volume based on the frame-to-volume registration can provide a comprehensive guidance view for cardiac interventional surgery. However, cardiac ultrasound ...

Radiance fields have demonstrated impressive performance in synthesizing lifelike 3D talking heads. However, due to the difficulty in fitting steep appearance changes, the prevailing paradigm that presents facial motions by directly modifying ...

Fine-grained sentiment analysis involves extracting and organizing sentiment elements from textual data. However, existing approaches often overlook issues of category semantic inclusion and overlap, as well as inherent structural patterns within ...

In this work, we investigate the problem of synthesizing a talking face video which should be synchronized with a target speech segment. Although there has been significant progress on this task, the most successful approaches are still those that ...

Along with the prevalent use of deep neural networks (DNNs), concerns have been raised on the security threats from DNNs such as backdoors in the network. While neural network repair methods have shown to be effective for fixing the defects in DNNs, they ...

Efficient and accurate evaluation of Large Language Models (LLMs) is essential for progress in the field of natural language processing. To address this, our paper introduces Transitive Merge Sort (TMS), a novel method that harnesses the ...

Graph Neural Networks (GNNs) have excelled in various graph-based applications. Recently, knowledge distillation (KD) has provided a new approach to further boost GNNs performance. However, in the KD process, the GNN student may encounter noise ...$\mathrm{}$

This paper proposes a blockchain-based scheme, focusing on anonymous identity authentication and data aggregation, for safer and more reliable bidirectional communication between the utility company and power consumers based on Advanced Metering ...

• Propose a virtual reality (VR) mapping method for the semi-occluded orchard environment.
• Develop a remote operating system for validating VR maps.
• Demonstrate the accuracy and semanticity of the constructed VR map.

The unstructured nature of orchard environments presents significant challenges for autonomous navigation of orchard robots. Teleoperation, combined with virtual reality (VR), has emerged as a promising solution to overcome the limitations of on-...

The fraudulent insurance claim is critical for the insurance industry. Insurance companies or agency platforms aim to confidently estimate the fraud risk of claims by gathering data from various sources. Although more data sources can improve the ...

Customer segmentation plays a crucial role in credit risk assessment by dividing users into specific risk levels based on their credit scores. Previous methods fail to comprehensively consider the stability in the segmentation process, resulting in ...

Autoscaling is a critical mechanism in cloud computing, enabling the autonomous adjustment of computing resources in response to dynamic workloads. This is particularly valuable for co-located, long-running applications with diverse workload patterns. ...