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Deep learning (DL) based Wi-Fi sensing has witnessed great development in recent years. Although decent results have been achieved in certain scenarios, Wi-Fi based activity recognition is still difficult to deploy in real smart homes due to the limited ...

Remote sensing object detection (RSOD) encounters challenges in effectively extracting features of small objects in remote sensing images (RSIs). To alleviate these problems, we proposed a Multi-Scale Network for Object Detection in Remote ...

• The parallel structure combining pointwise and partial convolution effectively reduce the number of parameters.
• The integration of context modeling and residual modules can effectively enhance small object features.
• The improved ...

• Segment anything model is applied for the multi-modal retinal disease diagnosis.
• A multi-modal dataset containing paired OCT and fundus images is constructed.
• Anomaly simulation and prompt-tuning strategies are used to fine-tune ...

The fusion of optical coherence tomography (OCT) and fundus modality information can provide a comprehensive diagnosis for retinal artery occlusion (RAO) disease, where OCT provides the cross-sectional examination of the fundus image. Given multi-...

nial-of-Service (DoS) attacks at the execution layer represent one of the most severe threats to blockchain systems, compromising availability by depleting the resources of victims. To counteract these attacks, many blockchains have implemented unique ...

Zero-knowledge layer 2 protocols emerge as a compelling approach to overcoming blockchain scalability issues by processing transactions through the transaction finalization process. During this process, transactions are efficiently processed off the main ...

UWB ranging systems have been adopted in many critical and security sensitive applications due to its precise positioning and secure ranging capabilities. We present a practical jamming attack, namely UWBAD, against commercial UWB ranging systems, which ...

As a promising approach, Clustered Federated Learning (CFL) enables personalized model aggregation for heterogeneous clients. However, facing dynamic and open edge networks, previous CFL rarely considers the impact of dynamic client data on clustering ...

As an unnoticed specialized task in image restoration, rain-by-snow weather removal aims to eliminate the complicated coexisting rain streaks and snow particles. In this work, we propose a simple attention-based sampling cross-hierarchy ...

• We first focus on rain-by-snow weather-degraded image restoration.
• We propose a simple attention-based sampling cross-hierarchy Transformer.
• We demonstrate that cross-stage progression is crucial for performance improvement.
• ...

With the development of blockchain technology, smart contracts have become an important component of blockchain applications. Despite their crucial role, the development of smart contracts may introduce vulnerabilities and potentially lead to severe ...

Given the significant differences between domains, current unpaired learning methods struggle to accurately map the relationship between rainy and clear images. To this end, we introduce a neural Schrödinger bridge (NSB) for unpaired real-world ...

Existing unpaired image deraining approaches face challenges in accurately capture the distinguishing characteristics between the rainy and clean domains, resulting in residual degradation and color distortion within the reconstructed images. To this end,...

Warning: Please note that this article contains potential harmful or offensive content. This content is only for the evaluating and analysis of LLMs and does not imply any intention to promote criminal activities.

The emergence of Large Language Models (...

In recent years, with the rapid development of robotics and computer technology, more and more robots have been integrated into people's lives. In nature, quadrupeds use vision to perform precise and flexible movements. Imitating their vision-based motor ...

Metamaterials are a class of artificial materials that have exceptional physical properties that do not exist in nature. They are widely used in various fields, such as electromagnetics, optics, and acoustics. However, designing metamaterials can ...

Move, a programming language for smart contracts, stands out for its focus on security. However, the practical security efficacy of Move contracts remains an open question. This work conducts the first comprehensive empirical study on the security of ...

Large Language Models (LLMs) specialized in code have shown exceptional proficiency across various programming-related tasks, particularly code generation. Nonetheless, due to its nature of pretraining on massive uncritically filtered data, prior studies ...

Smart contract developers frequently seek solutions to developmental challenges on Q&A platforms such as Stack Overflow (SO). Although community responses often provide viable solutions, the embedded code snippets can also contain hidden vulnerabilities. ...

Symbolic execution has proven effective for code analytics in smart contracts. However, for smart contracts, existing symbolic tools use multiple-transaction symbolic execution, which differs from traditional symbolic tools and also exacerbates the path ...

Generalist Large Language Models (LLMs), such as GPT-4, have shown considerable promise in various domains, including medical diagnosis. Rare diseases, affecting approximately 300 million people worldwide, often have unsatisfactory clinical diagnosis ...

• Comprehensive review of non-driven irradiance estimation methods.
• Detail analysis of the of IV-G and I-G models.
• Assessment of estimation models using 37 climatic patterns.
• MPPT accuracry is proporionate to irradiance estimation ...

This research investigates a low-cost method for estimating irradiance. The approach uses maximum power point tracking (MPPT) to easily estimate irradiance in a Photovoltaic (PV) system. Two main explicit mathematical models "IV-G" and "I-G" are ...