Search Results

In the federated learning (FL) research field, current research is confronted with several pivotal challenges, e.g., data privacy, model utility and communication efficiency. Furthermore, these challenges are further amplified by statistical data ...

• An end-to-end local adaptive compressed learning strategy is designed.
• Just a small amount of noise can provide stronger data privacy guarantee.
• Additional heterogeneity induced by Gaussian differential privacy can be mitigated.

In end-to-end image fusion models, the loss function significantly impacts performance. However, most loss functions treat salient and background regions in source images equally, failing to distinguish complementary areas in multimodal images. ...

• Implementing multidimensional flexibly collaborative fusion between multimodal image.
• Designed loss function of sum of correlation differences to improve interpretability.
• Crafted pixel-wise contrast method to adaptively generating ...

• The risk recognition for power operation safety with consideration the specific operation scene.
• Utilizing global visual features and spatial interaction features for scene understanding.
• Propose a method for extracting spatial ...

Risk identification in power operations is crucial for both personal safety and power production. Existing risk identification methods mainly use target detection models to identify the common risks but the scene specificity of risk occurrence. ...

In this paper, we consider a cooperative sensing framework in the context of future multi-functional network with both communication and sensing ability, where one base station (BS) serves as a sensing transmitter and several nearby BSs serve as sensing ...

Recently, tensor-based multi-view subspace clustering methods have shown promising results. Despite the impressive clustering performance, most clustering methods still face the following challenges: 1) the expensive computational burden caused by complex ...

Pyramid Temporal Hierarchy Network (PTH-Net) is a new paradigm for dynamic facial expression recognition, applied directly to raw videos, without face detection and alignment. Unlike the traditional paradigm, which focus only on facial areas and often ...

In pharmaceutical arena, various computational methods especially the receptor-based virtual screening has played an important role in improving the success ratio of drug discovery. Numerous researches have been reported from 1990 to 2024. ...

Cell-cell communication across multiple cell types and tissues strictly governs the proper functioning of metazoans and extensively relies on interactions between secreted ligands and cell-surface receptors. Understanding how the cells interact and ...

We developed PathActMarker, an R package for inferring pathway activity of complex diseases. The package integrates widely used normalization methods for gene expression data and provides pathway data from six sources. Meanwhile, eight state-of-...

Both clinical images and metadata are the foundation of clinical diagnosis, effectively fusing these two resources is a major difficulty in the detection of skin cancer. Even though existing fusion methods produced better fusion outcomes, they ...

• Implementing multidimensional collaboration between metadata and image features.
• Designed a non-enhanced manner to promote convergence based on contrast learning.
• Introduced a spatial-wise fusion method between metadata and image ...

This paper presents a linear implicit scheme for numerically solving the phase field crystal (PFC) equation. The scheme is constructed by the scalar auxiliary variable (SAV) approach and the leapfrog scheme in temporal direction. The proposed ...

The primary method for news recommendations revolves around leveraging the user’s browsing history to gauge their interests. Existing models prioritize analyzing news content to infer user interests, ignoring the role of label category information ...

• Introduced the several advanced artificial intelligence (AI) technologies.
• AI is increasingly being adopted to enhance the freshness of fruits and vegetables in the supply chain.
• AI will realize adaptive preservation control and ...

Fresh fruits and vegetables are characterized by high water content, perishability and strong seasonality. In the process of supply chain, it is easy to lead to the decrease of freshness. Artificial intelligence (AI) technology is considered as ...

As complex multi-omics data in the medical field tend to be multi-modal. Integrating these multimodal information into novel disease diagnosis models has become challenging. However, previous methods mainly focus on single omics, which cannot ...

Ocean tide loading (OTL) displacements observed by the Global Navigation Satellite System (GNSS) are generally less accurate for solar (S2 and P1) and lunisolar (K2 and K1) tidal constituents than for lunar tidal constituents (M2, N2, O1 and Q1). ...

The automatic classification of histopathological images plays a crucial role in cancer diagnosis. However, most existing medical image classification studies based on Capsule Network (CapsNet) suffer from issues such as overly localized feature ...$$$$$$$$

Medical image fusion (MIF) aims to integrate complementary information from multimodal images, generating a single fused image for enhanced applications in clinical diagnosis, preoperative planning. However, existing MIF models primarily focus on ...

Accurate wind speed forecasting holds the potential to optimize wind farm design and enhance the utilization of wind energy resources. However, the majority of current research has encountered three issues: (1) Feature selection is independent of ...

This paper investigates the fast chemical diffusion limit from a parabolic-parabolic Keller-Segel system to the corresponding parabolic-elliptic Keller-Segel system by constructing approximate solutions with an appropriate order via an asymptotic ...