Integrated sensing and communication (ISAC) is a promising technique to increase spectral efficiency and support various emerging applications by sharing the spectrum and hardware between these functionalities. Howeve...
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Integrated sensing and communication (ISAC) is a promising technique to increase spectral efficiency and support various emerging applications by sharing the spectrum and hardware between these functionalities. However, the traditional ISAC schemes are highly dependent on the accurate mathematical model and suffer from the challenges of high complexity and poor performance in practical scenarios. Recently, artificial intelligence (AI) has emerged as a viable technique to address these issues due to its powerful learning capabilities, satisfactory generalization capability, fast inference speed, and high adaptability for dynamic environments, facilitating a system design shift from model-driven to data-driven. Intelligent ISAC, which integrates AI into ISAC, has been a hot topic that has attracted many researchers to investigate. In this paper, we provide a comprehensive overview of intelligent ISAC, including its motivation, typical applications, recent trends, and challenges. In particular, we first introduce the basic principle of ISAC, followed by its key techniques. Then, an overview of AI and a comparison between model-based and AI-based methods for ISAC are provided. Furthermore, the typical applications of AI in ISAC and the recent trends for AI-enabled ISAC are reviewed. Finally, the future research issues and challenges of intelligent ISAC are discussed.
The growing realm of blockchain technology has captivated researchers and practitioners alike with its promise of decentralized, secure, and transparent transactions. This paper presents a comprehensive survey and ana...
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As the adoption of explainable AI(XAI) continues to expand, the urgency to address its privacy implications intensifies. Despite a growing corpus of research in AI privacy and explainability, there is little attention...
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As the adoption of explainable AI(XAI) continues to expand, the urgency to address its privacy implications intensifies. Despite a growing corpus of research in AI privacy and explainability, there is little attention on privacy-preserving model explanations. This article presents the first thorough survey about privacy attacks on model explanations and their countermeasures. Our contribution to this field comprises a thorough analysis of research papers with a connected taxonomy that facilitates the categorization of privacy attacks and countermeasures based on the targeted explanations. This work also includes an initial investigation into the causes of privacy leaks. Finally, we discuss unresolved issues and prospective research directions uncovered in our analysis. This survey aims to be a valuable resource for the research community and offers clear insights for those new to this domain. To support ongoing research, we have established an online resource repository, which will be continuously updated with new and relevant findings.
In the realm of low-level vision tasks,such as image deraining and dehazing,restoring images distorted by adverse weather conditions remains a significant *** emergence of abundant computational resources has driven t...
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In the realm of low-level vision tasks,such as image deraining and dehazing,restoring images distorted by adverse weather conditions remains a significant *** emergence of abundant computational resources has driven the dominance of deep Convolutional Neural Networks(CNNs),supplanting traditional methods reliant on prior ***,the evolution of CNN architectures has tended towards increasing complexity,utilizing intricate structures to enhance performance,often at the expense of computational *** response,we propose the Selective Kernel Dense Residual M-shaped Network(SKDRMNet),a flexible solution adept at balancing computational efficiency with network accuracy.A key innovation is the incorporation of an M-shaped hierarchical structure,derived from the U-Net framework as M-Network(M-Net),within which the Selective Kernel Dense Residual Module(SDRM)is introduced to reinforce multi-scale semantic feature *** methodology employs two sampling techniques-bilinear and pixel unshuffled and utilizes a multi-scale feature fusion approach to distil more robust spatial feature map *** the reconstruction phase,feature maps of varying resolutions are seamlessly integrated,and the extracted features are effectively merged using the Selective Kernel Fusion Module(SKFM).Empirical results demonstrate the comprehensive superiority of SKDRMNet across both synthetic and real rain and haze datasets.
Early detection of any disease and starting its treatment in this early stage are the most important steps in case of any life-threatening disease. Stroke is not an exception in this regard which is one of the leading...
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In today’s era, smartphones are used in daily lives because they are ubiquitous and can be customized by installing third-party apps. As a result, the menaces because of these apps, which are potentially risky for u...
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Accurate crowd counting in natural images has become increasingly attractive owing to its numerous real-world applications, e.g., crowd analysis and video surveillance. Despite significant progress in crowd counting [...
Accurate crowd counting in natural images has become increasingly attractive owing to its numerous real-world applications, e.g., crowd analysis and video surveillance. Despite significant progress in crowd counting [1,2], challenges(such as scale variation and background clutter) *** fully utilize spatial information, existing crowd counting approaches [3, 4] mainly estimate a density map, where point annotations are smoothed via a Gaussian kernel to generate probabilities indicating the presence of a crowd.
Package delivery via ridesharing provides appealing benefits of lower delivery cost and efficient vehicle *** existing ridesharing systems operate the matching of ridesharing in a centralized manner,which may result i...
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Package delivery via ridesharing provides appealing benefits of lower delivery cost and efficient vehicle *** existing ridesharing systems operate the matching of ridesharing in a centralized manner,which may result in the single point of failure once the controller breaks down or is under *** tackle such problems,our goal in this paper is to develop a blockchain-based package delivery ridesharing system,where decentralization is adopted to remove intermediaries and direct transactions between the providers and the requestors are *** complete the matching process under decentralized structure,an Event-Triggered Distributed Deep Reinforcement Learning(ETDDRL)algorithm is proposed to generate/update the real-time ridesharing orders for the new coming ridesharing requests from a local *** results reveal the vast potential of the ETDDRL matching algorithm under the blockchain framework for the promotion of the ridesharing ***,we develop an application for Android-based terminals to verify the ETDDRL matching algorithm.
From a medical perspective,the 12 leads of the heart in an electrocardiogram(ECG)signal have functional dependencies with each ***,all these leads report different aspects of an *** differences lie in the level of hig...
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From a medical perspective,the 12 leads of the heart in an electrocardiogram(ECG)signal have functional dependencies with each ***,all these leads report different aspects of an *** differences lie in the level of highlighting and displaying information about that *** example,although all leads show traces of atrial excitation,this function is more evident in lead II than in any other *** this article,a new model was proposed using ECG functional and structural dependencies between heart *** the prescreening stage,the ECG signals are segmented from the QRS point so that further analyzes can be performed on these segments in a more detailed *** mutual information indices were used to assess the relationship between *** order to calculate mutual information,the correlation between the 12 ECG leads has been *** output of this step is a matrix containing all mutual ***,to calculate the structural information of ECG signals,a capsule neural network was implemented to aid physicians in the automatic classification of cardiac *** architecture of this capsule neural network has been modified to perform the classification *** the experimental results section,the proposed model was used to classify arrhythmias in ECG signals from the Chapman *** evaluations showed that this model has a precision of 97.02%,recall of 96.13%,F1-score of 96.57%and accuracy of 97.38%,indicating acceptable performance compared to other state-of-the-art *** proposed method shows an average accuracy of 2%superiority over similar works.
Unmanned Aerial Vehicles(UAvs)as aerial base stations to provide communication services for ground users is a flexible and cost-effective paradigm in ***,dynamic resource allocation and multi-connectivity can be adopt...
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Unmanned Aerial Vehicles(UAvs)as aerial base stations to provide communication services for ground users is a flexible and cost-effective paradigm in ***,dynamic resource allocation and multi-connectivity can be adopted to further harness the potentials of UAVs in improving communication capacity,in such situations such that the interference among users becomes a pivotal disincentive requiring effective *** this end,we investigate the Joint UAV-User Association,Channel Allocation,and transmission Power Control(J-UACAPC)problem in a multi-connectivity-enabled UAV network with constrained backhaul links,where each UAV can determine the reusable channels and transmission power to serve the selected ground *** goal was to mitigate co-channel interference while maximizing long-term system *** problem was modeled as a cooperative stochastic game with hybrid discrete-continuous action space.A Multi-Agent Hybrid Deep Reinforcement Learning(MAHDRL)algorithm was proposed to address this *** simulation results demonstrated the effectiveness of the proposed algorithm and showed that it has a higher system utility than the baseline methods.
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