The increasing use of smartphones for capturing documents in various real-world conditions has underscored the need for robust document localization technologies. Current challenges in this domain include handling diverse document types, complex ...

Generative models are widely utilized to model the distribution of fused images in the field of infrared and visible image fusion. However, current generative models based fusion methods often suffer from unstable training and slow inference ...

In the imprecise investment environment, there are many indeterminate factors impacting security returns. This paper introduces a portfolio optimization problem where cross-entropy is utilized to control portfolio risk within the framework of ...

Over the past decade, Open Source Software (OSS) has experienced rapid growth and widespread adoption, attributed to its openness and editability. However, this expansion has also brought significant security challenges, particularly introducing and ...

Density Peaks Clustering (DPC) is a well-known clustering technique in the data mining field with fewer parameters as well as no iteration. However, when dealing with datasets containing multiple peaks, DPC may subjectively choose the wrong ...

Visual Geo-localization (VG) refers to the process to identify the location described in query images, which is widely applied in robotics field and computer vision tasks, such as autonomous driving, metaverse, augmented reality, and SLAM. In fine-...

Temporal language grounding in videos aims to ground one video segment in an untrimmed video based on a given sentence query. The main challenge in this task lies in how to align the video and textual modalities effectively. Most existing methods ...

Transmission Control Protocol (TCP) controlling congestion by peer-to-peer is challenging to handle communication with numerous concurrent TCP flows and heavy traffic loads. Therefore, TCP requires the active queue management (AQM) to assist in ...

In the distributed machine learning field, federated learning (FL) serves as a highly effective framework for dismantling data silos and integrating data from multiple sources. However, the flourishing of FL still encounters significant ...

• A fine-grained Cryptography-TEE hybrid security model for multi-party cooperative computation scenario is defined.
• A series of TEE-assisted secure computation protocols are designed to achieve secure and lossless non-linear operations.

Federated learning (FL), as a distributed machine learning paradigm, essentially promises that multiple parties can jointly train the model collaboratively without sharing local data. Recent research demonstrates that the adversary can deduce the ...

• A stabilized peridynamic correspondence material model for axisymmetric ablation and fracture problems is proposed.
• A strain energy density decomposition method is adopted to distinguish effect of different deformations.
• A novel ...

A stabilized peridynamic correspondence material model for axisymmetric problems (SPD-CMM-A) is proposed in this work to effectively simulate the ablation and ductile fracture behaviors of metals under high temperatures. To quantify the damage ...

Real-time service (RTS) products are an important guarantee for real-time precise point positioning (RT-PPP), and the RTS outages caused by loss of network connection are a concern. In this paper, a multivariate CNN-LSTM model is proposed for ...

In today’s digital and intelligent environment, the research on authentication technology has become an important branch in the field of information security. This paper introduces an identity verification method that utilizes user profiles on the ...

Low-cost single-frequency receivers are increasingly applied to high-precision positioning in support of high-performance GNSS market applications. However, frequent and multiple small cycle slips (CS) detection and repair is a limiting factor for ...

Although In-Context Learning (ICL) brings remarkable performance gains to Large Language Models (LLMs), the improvements remain lower than fine-tuning on downstream tasks. This paper introduces Multi-Modal In-Context Tuning (MMICT), a novel multi-modal ...

As an important fund for equipment support, the use effect of equipment maintenance expenses directly affects the generation of military combat effectiveness. In view of the shortcomings in the current research on the performance evaluation of military ...

As an important fund to support the maintenance and restoration of combat effectiveness of equipment, strengthening the risk management of equipment maintenance costs is of great significance. As the top priority of risk management, risk identification ...

Multicast serves as an important approach for one-to-many communication in data center networks. To reduce overhead and improve scalability, bloom filters are employed in current multicast approaches to store forwarding ports of switches. However, the ...

This paper introduces a method incorporating a multi-attention mechanism with a Bidirectional Long Short-Term Memory Network (BiLSTM) structure, aimed at predicting the binding probability between peptides and major histocompatibility complex (...

Boundary box regression is a crucial step in object detection, directly influencing the model's ability to accurately locate objects. Traditional Intersection over Union (IoU) loss functions struggle to provide effective gradient information when ...