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MKD-YOLO: Multi-Scale and Knowledge-Distilling YOLO for Efficient PPE Compliance Detection
Juntao Zan;Yang Fang;Qilie Liu;Uswah Khairuddin;Yan Li;Kaiwei Sun
ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Year: 2025 | Conference Paper |
YOLO-based models are widely used for personal protective equipment (PPE) compliance detection due to their excellent detection performance and efficiency. However, most YOLO models are not competent for detection tasks in complex industrial scenarios such as remote surveillance and extremely small targets. In addition, there is a lack of effective model lightweighting and knowledge transfer appro...Show More
Communication-Efficient Federated Learning for Large-Scale Multiagent Systems in ISAC: Data Augmentation With Reinforcement Learning
Wenjiang Ouyang;Qian Liu;Junsheng Mu;Anwer AI-Dulaimi;Xiaojun Jing;Qilie Liu
Integrated sensing and communication (ISAC) has attracted great attention with the gains of spectrum efficiency and deployment costs through the coexistence of sensing and communication functions. Meanwhile, federated learning (FL) has great potential to apply to large-scale multiagent systems (LSMAS) in ISAC due to the attractive privacy protection mechanism. Nonindependent identically distributi...Show More
Integrating terrestrial and non-terrestrial networks can provide ubiquitous global communications for 6G Internet of Things (IoT) services. However, integrated terrestrial and non-terrestrial networks (ITNTNs) face enormous challenges, such as complex network environments, differentiated service demands, and multi-layer heterogeneous networks. By leveraging the powerful driving force of edge intel...Show More
Optimizing Tradeoff Between Learning Speed and Cost for Federated-Learning-Enabled Industrial IoT
Long Zhang;Suiyuan Wu;Haitao Xu;Qilie Liu;Choong Seon Hong;Zhu Han
IEEE Internet of Things Journal
Cited by: Papers (1)
A combination of Industrial Internet of Things (IIoT) and federated learning (FL) is deemed as a promising solution to realize Industry 4.0 and beyond. However, scheduling more IIoT devices engaged in FL contributes to accelerated learning speed, but resulting in increased learning cost in terms of energy consumption and model accuracy reduction. In this article, we investigate the tradeoff betwee...Show More
Adaptive MARL-based Joint Cooperative Caching and Resource Allocation for Deep Edge Networks
2023 IEEE 98th Vehicular Technology Conference (VTC2023-Fall)
Year: 2023 | Conference Paper |
With the rapid development of mobile communications services and applications, deep edge networks (DENs) have become a new paradigm for addressing data traffic and network delay by combining mobile edge computing (MEC) and artificial intelligence (AI). In this network, edge caching can provide low-latency and reliable services in resource-constrained scenarios by caching content in the wireless ac...Show More
Research on Vehicular External Network Intrusion Detection System Based on Ensemble Learning
2023 IEEE 98th Vehicular Technology Conference (VTC2023-Fall)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
With the development of the Internet of Vehicles(IoV), the combination of networks and vehicles has brought great convenience to people. However, hackers can attack vehicles through technical loopholes in the external network, which seriously affects the driving safety of vehicles. In this paper, we propose a new intrusion detection system (IDS) framework named the Leading Model and Confidence Dec...Show More
Joint Computation Offloading and Power Allocation Strategy in NOMA-Based Dynamic MEC Network Assisted by RIS
2023 IEEE 34th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)
Year: 2023 | Conference Paper |
Mobile edge computing (MEC) holds great promise as an effective solution that empowers resource-constrained intelligent applications to transfer computation-intensive operations to neighboring edge servers. To realize its potential, reconfigurable intelligent surface (RIS) provides high spectral and energy efficiency, can effectively reduce the computation costs. This paper discusses a joint compu...Show More
Joint Task Offloading and Resource Allocation for RIS-assisted UAV for Mobile Edge Computing Networks
2023 IEEE/CIC International Conference on Communications in China (ICCC)
Year: 2023 | Conference Paper |
Cited by: Papers (4)
Unmanned aerial vehicles (UAVs) can assist mobile edge computing (MEC) networks to enhance ground users’ communication in emergencies. However, how to provide good quality of service (QoS) to ground users for a long time is still a tricky problem due to the limited battery capacity and computing power of UAVs. Therefore, we take advantage of reconfigurable intelligent surface (RIS) for UAV-MEC net...Show More
Digital Twin-Assisted Edge Computation Offloading in Industrial Internet of Things With NOMA
Long Zhang;Han Wang;Hongmei Xue;Hongliang Zhang;Qilie Liu;Dusit Niyato;Zhu Han
Integrating digital twins (DTs) and multi-access edge computing (MEC) is a promising technology that realizes edge intelligence in 6 G, which has been recognized as the key enabler for Industrial Internet of Things (IIoT). In this paper, we explore a DT-assisted MEC system for the IIoT scenario where a DT server is created as a virtual representation of the physical MEC server, via estimating the ...Show More
Energy-Efficient Joint Computation Offloading and Resource Allocation Strategy for ISAC-Aided 6G V2X Networks
Integrated sensing and communications (ISAC) is a pillar technology of 6G to enable intelligent environment awareness and hardware cost efficiencies. In ISAC-aided 6G vehicle-to-everything (V2X) networks, the perception data fusion from multiple sources can make a reliable and efficient data sharing to guarantee driving safety. However, the contradiction between task delay requirement and energy c...Show More
Spatiotemporal Pyramid Aggregation and Graph Attention for Scene Perception and Tajectory Prediction
Jianhong Zou;Ting Zhao;Bei Luo;Yihui Cui;Weihua Ouyang;Qilie Liu
2022 6th Asian Conference on Artificial Intelligence Technology (ACAIT)
Year: 2022 | Conference Paper |
In the autonomous driving system, accurate scene perception and trajectory prediction are critical for collision avoidance and path planning of autonomous vehicles. This paper proposes a scene perception and trajectory prediction method based on graph attention mechanism to learn semantic and interaction information based on bird eye’s view (BEV) map. The method includes spatiotemporal pyramid net...Show More
Multifactor Recommendation-based Video Caching Strategy in Mobile Edge Computing
2022 IEEE 21st International Conference on Ubiquitous Computing and Communications (IUCC/CIT/DSCI/SmartCNS)
Year: 2022 | Conference Paper |
Cited by: Papers (1)
Mobile edge computing (MEC) can provide users with high-quality video services by placing computing and storage capacity close to the user. Transferring large size video files usually consumes more time and energy, and the emergence of edge caching can effectively solve this problem. Current caching schemes generally consider the impact of only one or two factors among attributes such as ratings a...Show More
Secure Charging Scheduling Strategy for Electric Vehicles Based on Blockchain
2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)
Year: 2022 | Conference Paper |
Cited by: Papers (2)
In the Vehicle-to-grid (V2G) network, two-way energy transactions can be performed between electric vehicles (EVs) and charging stations (CSs), which are an important technology to support greener and energy-saving networks. As the EV ownership rate continues to rise, the unbalanced loads of CSs in some regions may cause undermine the stability of the power grid system. This paper proposes a CS ma...Show More
Mobility-Aware Computation Offloading for Cloud-Assisted Mobile Edge Computing in Vehicular Networks
2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)
Year: 2022 | Conference Paper |
Cited by: Papers (1)
Mobile Edge Computing (MEC) is a promising solution for vehicular task offloading to meet the stringent delay and high-reliability requirements. In addition, cloud-assisted MEC can further improve resource utilization of MEC and cloud computing server. However, the current cloud-assisted MEC offloading schemes have high algorithm complexity and a single optimization target (e.g., latency). At the ...Show More
Robust and Outage-Constrained Energy Efficiency Optimization in RIS-Assisted NOMA Networks
Yanan Xin;Yongjun Xu;Qilie Liu;Chongwen Huang;Dong Huang;Jihua Zhou
2022 IEEE 95th Vehicular Technology Conference: (VTC2022-Spring)
Year: 2022 | Conference Paper |
Cited by: Papers (1)
Robustness and energy efficiency (EE) are of crucial importance in reconfigurable intelligent surface (RIS)-assisted wireless communication networks. However, a large portion of the current works assume that perfect channel state information (CSI) can be obtained, which is impractical because of the passive features of the RIS and the lack of radio frequency chains at the RIS. To handle this issue...Show More
Energy-Efficiency Computation Offloading Strategy in UAV Aided V2X Network With Integrated Sensing and Communication
Integrated Sensing and Communications (ISAC) technology can jointly design radio sensing and communication functionalities, which enable 6G Ere to have the ability to “see” the physical world rather than communication-only. Benefitting from ISAC, vehicular-to-everything (V2X) networks may efficiently complete high-precision traffic environment perception. Furthermore, with the assistance of flexib...Show More
Lyapunov Optimization-Based Trade-Off Policy for Mobile Cloud Offloading in Heterogeneous Wireless Networks
In order to improve mobile users’ service experience, mobile cloud computing (MCC) is promoted. Although MCC can alleviate the burdens of Smart mobile devices (SMDs) by offloading computation-intensive applications to the cloud, it also aggravates computing and storage overheads in cloud centers and bandwidth overhead on wireless links for offloading workloads of mobile users. Therefore, we should...Show More
Energy-efficient Resource Allocation for Secure IRS Networks with an Active Eavesdropper
2020 IEEE/CIC International Conference on Communications in China (ICCC)
Year: 2020 | Conference Paper |
Cited by: Papers (4)
In this paper, in order to solve poor communication problems under the long-distance transmission and secure communication, an energy-efficient maximization based resource allocation (RA) algorithm is proposed to improve system energy efficiency (EE) and information security for secure intelligent reflecting surface-based cellular networks under an active eavesdropper. Firstly, a nonlinear RA mode...Show More
Robust Resource Allocation and Transmission Time Optimization for OFDMA-based Heterogeneous Networks
2019 11th International Conference on Wireless Communications and Signal Processing (WCSP)
Year: 2019 | Conference Paper |
Cited by: Papers (1)
To improve transmission efficiency and robustness, we investigate robust energy efficiency (EE)-based maximization power allocation and time optimization problem in orthogonal frequency division multiple access (OFDMA) based heterogeneous networks under channel uncertainties. The non-convex optimization problem is decomposed into three subproblems: subcarrier allocation, transmission time optimiza...Show More
Resource Allocation for OFDMA-Based Cognitive Networks: An Interference-Efficient Perspective
2019 IEEE 90th Vehicular Technology Conference (VTC2019-Fall)
Year: 2019 | Conference Paper |
In this paper, the interference-efficient based resource allocation for uplink transmission in an OFDMA-based cognitive radio network is studied. The interference efficiency (IE) is defined as the total data rate of secondary users (SUs) over sum interference power imposed on primary users (PUs). The objective is to maximize the total IE of SUs subject to transmit power constraints of SUs, subcarr...Show More
Energy-Efficient Deployment and Adaptive Sleeping in Heterogeneous Cellular Networks
Yun Li;He Zhang;Junwei Wang;Bin Cao;Qilie Liu;Mahmoud Daneshmand
This paper focuses on energy efficiency that is a key performance metric in heterogeneous cellular networks to two key areas. First, based on the Poisson point process distributions of small-cell base stations (SBSs) and macrocell base stations (MBSs), the energy-efficiency model is formulated, and the effect of base stations’ distribution on energy efficiency is analyzed. For maximizing energy ef...Show More
Resources Allocation in Multicell D2D Communications for Internet of Things
IEEE Internet of Things Journal
Cited by: Papers (40)
Device-to-device (D2D) communication can realize the direct communication between mobile users with short distance. It is an enabling technology for realizing Internet of Things in the long-term evolution-advanced system to the future fifth-generation mobile communication system. D2D communication multiplexes the licensed spectrum of cellular users (CUs) to D2D users (DUs) to improve resource util...Show More
A Novel Game Based Incentive Strategy for Opportunistic Networks
2015 IEEE Global Communications Conference (GLOBECOM)
Year: 2015 | Conference Paper |
Cited by: Papers (7)
Opportunistic networks are a emerging networks characterized by frequent network partitions, high bit error ratio and random topology instability, where the message propagation depends on the cooperation of nodes to fulfill a "store-carry-forward" fashion. Due to the constrained energy, memory and processing capacity, some individual nodes may behave selfishly, or even maliciously, which will intr...Show More
Collaborative Sleeping Scheme for Femtocell Networks
2013 IEEE International Conference on Green Computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical and Social Computing
Year: 2013 | Conference Paper |
Cited by: Papers (5)
Energy consumption is rising sharply due to the large deployment of the Home Base Stations (HeNBs) by subscribers, it not only brings the cost burden to operators, but also brings the pollution to the environment. Now the energy efficiency (EE) researches on HeNB are based on the algorithms about the adaptive power or the spectrum utilization, rarely consider the collaborative sleeping scheme to s...Show More
Robust adaptive fetal heart rate estimation for single-channel abdominal ECG recording
2012 5th International Conference on BioMedical Engineering and Informatics
Year: 2012 | Conference Paper |
Cited by: Papers (2)
Although doppler ultrasound is now routinely applied to the detection of fetal heart rate (FHR) for the assessment of perinatal fetal well-being, it is unsuitable for long-term at-home monitoring due to its transmission of ultrasound beam directly to the fetal heart and the requirement of frequent repositioning the ultrasound probe. As a non-invasive diagnostic tool, fetal Electrocardiogram (FECG)...Show More
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