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2022 IEEE International Conference on Multimedia and Expo, ICME 2022

作者： Shen, Yang Sun, Xuhao Wei, Xiu-Shen Hu, Hanxu Chen, Zhipeng School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China Xidian University State Key Laboratory of Integrated Services Networks Xi'an China Nanjing University State Key Laboratory for Novel Software Technology Nanjing China University of Edinburgh Edinburgh United Kingdom Beijing China

ISBN: (数字)9781665485630

ISBN: (纸本)9781665485630

In this paper, we propose a simple but effective method for dealing with the challenging fine-grained cross-modal retrieval task where it aims to enable flexible retrieval among subor-dinate categories across different modalities. Specifically, in order to enhance information interaction in different modalities for fine-grained objects, a channel mix method is developed and performed upon the channels of deep activations across dif-ferent modalities. After that, a 1 x 1 convolution is employed to aggregate the mixed channels into a unified feature vector. Moreover, equipped with a novel fine-grained cross-modal cen-ter loss, our method can further improve the intra-class separa-bility as well as inter-class compactness for multi-modalities. Experiments are conducted on the fine-grained cross-modal benchmark dataset and show our superiority over competing methods. Meanwhile, ablation studies also demonstrate the effectiveness of our proposals. © 2022 IEEE.

关键词： Computer vision

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Lightweight Small Target Detection Algorithm Based on YOLOv5 2

Lightweight Small Target Detection Algorithm Based on YOLOv5

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2nd International Conference on Applied Statistics, Computational Mathematics, and software engineering, ASCMSE 2023

作者： Song, Nan Wang, Ying Xin, Zhiyi Xin, Huili Liu, Tianxu Henan International Joint Laboratory of Theories and Key Technologies on Intelligence Networks Henan University Kaifeng475004 China Software Engineering Intelligent Information Processing Innovation Base-Subject Innovation Base of Henan Higher Universities Henan University Kaifeng475004 China Henan Provincial Communications and Transportation Dispatch and Command Center Zhengzhou450000 China

ISBN: (数字)9781510668195

ISBN: (纸本)9781510668188

To address the problems of current small target detection algorithms such as slow detection speed, high memory consumption, and not well applied to mobile devices, an improved lightweight small target detection algorithm MTGYOLOv5 is proposed based on YOLOv5s algorithm. firstly, MobileNet V3 is used instead of the backbone network to reduce the number of network parameters and increase the speed of operation. Secondly, the small target detection layer is added to the original network structure to enhance the detection capability of small targets. Finally, Ghost module is introduced to replace the commonly used convolutional kernel to ensure detection accuracy and further lightweighting. The improved algorithm was tested on the processed TinyPerson dataset. The experimental results show that the overall average accuracy of mAP of YOLOv5s algorithm is improved by 4.5%, the parameters are reduced by 1/2, the FPS is improved from 123.54 to 187.62, and the speed is enhenced by 51.87%. The algorithm effectively improves the detection speed while ensuring the detection accuracy. © 2023 SPIE.

关键词： Signal detection

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Intelligent Spectrum Management for UAV Swarm with Multiple Combat Missions: A DQN-Based Solution

Intelligent Spectrum Management for UAV Swarm with Multiple ...

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International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC

作者： Yukai Hou Zhijun Liu Fan Wang Lingyun Zhou Tao Shang Rongqing Zhang School of Software Engineering Tongji University Shanghai China School of Telecommunications Engineering Xidian University Xi’an China College of Electronics and Information Engineering South-Central Minzu University Wuhan China State Key Laboratory of Integrated Services Networks Xidian University Xi’an China

ISBN: (数字)9798331506896

ISBN: (纸本)9798331506902

In unmanned aerial vehicles(UAV) swarm combat, efficient management of electromagnetic spectrum resources is crucial to ensure the operational performance of UAV swarm. However, in the presence of external radiations, the spectrum interference and competition between UAV onboard communication, radar, reconnaissance, and jamming services greatly affect the combat effectiveness of UAV swarm. Besides, because of the heterogeneity and coupling of different services, traditional spectrum allocation methods lack flexibility and occupy many computing resources in the central nodes. In this paper, by setting the threshold and the utility function for each service, we model the multi-service spectrum scheduling as a joint utility maximization problem. Then, we propose an intelligent and lightweight spectrum management method based on deep Q-network for multi-service cooperative spectrum scheduling. By dynamically and collaboratively allocating spectrum resources, conflicts within and between services are greatly reduced. Extensive simulations demonstrate that the proposed approach provides robust and efficient multi-service spectrum management.

关键词： Processor scheduling Computational modeling Radar Reinforcement learning Reconnaissance Autonomous aerial vehicles Knowledge discovery Resource management Jamming Radio spectrum management

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Accurate Detection of Third-Party Library Version of IoT Firmware Based on GNN 3

Accurate Detection of Third-Party Library Version of IoT Fir...

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3rd International Conference on Artificial Intelligence, Big Data and Algorithms, CAIBDA 2023

作者： Guo, Jingdong Wang, Ying Wang, Zhuo Henan International Joint Laboratory of Theories and Key Technologies on Intelligence Networks Henan University Kaifeng475004 China Institute of Information Engineering Chinese Academy of Sciences Beijing China Software Eng. Intelligent Info. Proc. Innov. Base-Subj. Innovation Base of Henan Higher Universities Henan University Kaifeng475004 China

ISBN: (纸本)9781643684444

Third-party libraries are widely used in IoT firmware, and different versions of libraries have different vulnerabilities. Therefore, extracting versions of third-party libraries is of great significance for discovering known vulnerabilities of IoT devices. However, identifying the version of third-party library in IoT firmware is very challenging due to cross-architecture, cross-compiler, and cross-optimization options issues. To address this challenge, we present FirmAd, a GNN-based system that accurately detects third-party libraries' versions in IoT firmware. The system leverages a two-stage approach that calculates the similarity of different granularity features to obtain the final TPL version. We evaluate FirmAd on a large-scale dataset comprising 10,699 TPLs and achieve a version information identification accuracy of 92.68%, which is 8% higher than existing methods. © 2023 The Authors.

关键词： Firmware

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Enhancing Low-Latency and High-Reliability Data Forwarding for In-Vehicle Time-Sensitive networks

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IEEE Transactions on Vehicular Technology 2025年

作者： Sun, Haitong Zhang, Haijun Guan, Wanqing Liu, Xiangnan Ma, Hui Leung, Victor C.M. Hebei Key Laboratory of Space-Air-Ground Intelligent Communication China Beijing Engineering and Technology Research Center for Convergence Networks and Ubiquitous Services University of Science and Technology Beijing Beijing100083 China School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm11428 Sweden Department of Computer Science and Software Engineering Shenzhen University Shenzhen518061 China

To satisfy the low delay, low jitter, and high success rate requirements for in-vehicle networks, IEEE 802.1 Task Group proposed Time-Sensitive Networking (TSN), which has aroused increasing attention in managing time-critical services in networks. This paper resolves the following issue: how to minimize the worst-case response time (WCRT) of frame forwarding in TSN under no-wait scenarios to guarantee low-latency transmission, stability, and high success rate for in-vehicle TSN networks? Currently, some work resolves this problem by leveraging integer linear programming, and others apply heuristic methods to avoid the time complexity problem, but the success rate is affected since they are prone to get trapped in local optima. To reach a balance between time-complexity and success rate, a scheme named Frame Dynamic Priority Scheduling Mechanism (FDPSM) is proposed, where the frame dynamic priority levels are set up and frames are scheduled accordingly. The target is to maximize the success rate and minimize the WCRT for in-vehicle networks. We evaluate the proposed mechanism from aspects such as traffic forwarding time, size of windows, number of hops, and the network load, together with success rate and the simulation results demonstrate the advantages of the FDPSM for in-vehicle TSN networks. © 2025 IEEE. All rights reserved,

关键词： Integer programming

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Denoising Diffusion Model-Based Channel Estimation in IRS-Assisted ISAC Systems

Denoising Diffusion Model-Based Channel Estimation in IRS-As...

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International Conference on Wireless Communications and Signal Processing (WCSP)

作者： Lan Yi Jiansong Miao Tao Zhang Zhenhui Yuan Jiawen Kang Dusit Niyato Beijing Laboratory of Advanced Information Networks Beijing University of Posts and Telecommunications Beijing China School of Software Engineering Beijing Jiaotong University Beijing China School of Engineering University of Warwick UK School of Automation Guangdong University of Technology Guangzhou China School of Computer Science and Engineering Nanyang Technological University Singapore Singapore

ISBN: (数字)9798350390643

ISBN: (纸本)9798350390650

In Integrated Sensing and Communications (ISAC) systems assisted by Intelligent Reflecting Surfaces (IRS), precise channel estimation is crucial for optimal system performance and maximizing the potential benefits. The estimation problem, however, becomes intricate due to complex channel coupling and specific environmental conditions. This paper addresses these challenges by formulating channel estimation as a denoising problem and proposing a novel diffusion-based framework. This approach mitigates the impact of ill-posedness, which is typically problematic for general neural network (NN)-based techniques. By modeling the joint distribution and sampling from the learned posterior distribution, we accurately recover the channel coefficients from noisy pilot-based observations. Simulation results demonstrate significant performance improvements of the proposed method compared to both least-squares and NN-based benchmarks. Moreover, thanks to the carefully designed architecture and residual prediction strategy, the number of sampling steps in the diffusion reverse process is greatly reduced, enabling real-time CSI acquisition.

关键词： Wireless communication System performance Noise reduction Channel estimation Signal processing algorithms Estimation Artificial neural networks Integrated sensing and communication Prediction algorithms Diffusion models

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Imperceptible and Reliable Adversarial Attack 1

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4th International Conference on Frontiers in Cyber Security, FCS 2021

作者： Zhang, Jiawei Wang, Jinwei Luo, Xiangyang Ma, Bin Xiong, Naixue School of Computer and Software Engineering Research Center of Digital Forensics Ministry of Education Nanjing University of Information Science and Technology Nanjing210044 China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhenzhou450001 China Shandong Provincial Key Laboratory of Computer Networks and Qilu University of Technology Jinan250353 China Department of Computer Science and Mathematics Sul Ross State University AlpineTX79830 United States

ISBN: (数字)9789811905230

ISBN: (纸本)9789811905223

Deep neural networks are vulnerable to adversarial examples, which can fool classifiers by adding small perturbations. Various adversarial attack methods have been proposed in the past several years, and most of them add the perturbation in a "sparse" or "global" way. Since the number of pixels perturbed by the "sparse" method and the perturbation intensity of each pixel added by the "global" method are both small, the adversarial property can be destroyed easily. Finally, it makes the adversarial attack and the adversarial training based on these samples unreliable. To address this issue, we present an "pixel-wise" method which is somewhere in between the "sparse" or "global" way. First, the perception of human eyes to the error of different image regions is different. Second, image processing methods have different effects on the different areas of the image. Based on these two considerations, we propose an imperceptible and reliable adversarial attack method, which projects the perturbation to the different areas differently. Extensive experiments demonstrate our method can preserve the attack ability while maintaining good view quality. More importantly, the proposed projection can be combined with existing attack methods to generate a stronger generation algorithm which improves the robustness of adversarial examples. Based on the proposed method, the reliability of adversarial attacks can be greatly improved. © 2022, Springer Nature Singapore Pte Ltd.

关键词： Pixels

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Analysis of the Spatial Smoothing Influence on the Perfomance of 2D-MUSIC for Ultra-Dense networks

Analysis of the Spatial Smoothing Influence on the Perfomanc...

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Wave Electronics and its Application in Information and Telecommunication Systems (WECONF)

作者： Ilya Grishin Grigoriy Fokin Vladimir Sevidov Darina Okuneva Department of Communication Networks The Bonch-Bruevich SPbSUT Saint Petersburg Russia Laboratory of Software Defined Radio The Bonch-Bruevich SPbSUT Saint Petersburg Russia Department of Radio Engineering S.M. Budyonny VAS Saint Petersburg Russia Department of Software Engineering and Computer Facilities The Bonch-Bruevich SPbSUT Saint Petersburg Russia

In this paper, we analyze the spatial smoothing as a method of signal processing, preceding the algorithm for determining the direction of arrival of 2D-MUSIC signals. The purpose of the method is to compensate the possible coherence of signals coming from different user devices to the uniform rectangular antenna array of the base station of the ultra-dense network operating in the millimeter wavelength range. The results of computational experiments allow to estimate the dependence of the performance of the 2D-MUSIC algorithm to the spatial smoothing procedure.

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Covert Communication in Underlay Multi-Antenna Cognitive Radio networks

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IEEE Transactions on Cognitive Communications and Networking 2024年第3期11卷 1493-1507页

作者： Fan, Hongbin Yang, Weiwei Shi, Hui Pan, Gaofeng Si, Jiangbo Wang, Yutao Rong, Chuanzhen Army Engineering University of PLA College of Communications Engineering Nanjing210007 China Xiangnan University College of Computer and Artificial Intelligence Chenzhou423000 China Guilin University of Electronic Technology Guangxi Key Laboratory of Trusted Software Guilin541004 China Beijing Institute of Technology School of Cyberspace Science and Technology Beijing100081 China Xidian University State Key Laboratory of Integrated Services Networks Xi'an710100 China

In this paper, we investigated a multi-antenna covert communication in underlay cognitive radio networks (UCRNs), by considering both cases that Willie has the perfect and statistical channel state information (CSI) of the link from the secondary transmitter (ST) to the primary receiver (PR), respectively. Specifically, the optimal antenna of the secondary receiver (SR) is selected to receive the private information from ST, and then one of the remaining antennas is randomly selected to transmit jamming signals. The closed-form expressions of Willie's detection error probability, the average minimum detection error probability, the transmission outage probability and the maximum effective covert rate under both cases are derived. The maximum effective covert rate is obtained by optimising the maximum jamming power of SR. The numerical results show that the combined effect of the maximum interference tolerance of PR and the maximum interference power of SR provides the positive effective covert rate between ST and SR. It is further found that the maximum effective covert rate between ST and SR when Willie knows the perfect CSI of the ST-SR link is greater than that when Willie only knows the statistical CSI of the ST-SR link. © 2015 IEEE.

关键词： Jamming

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A Low Self-Noise Fiber Optic Gyroscope Based on Dual-polarization Configuration for Geophysical Rotation Sensing

A Low Self-Noise Fiber Optic Gyroscope Based on Dual-polariz...

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2021 Asia Communications and Photonics Conference, ACP 2021

作者： Chen, Yanjun Cao, Yuwen Wang, Wenbo He, Yan Zhou, Tong Li, Zhengbin State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Engineering and Computer Science Peking University Beijing100871 China School of Software and Microelectronics Peking University Beijing102600 China

A fiber optic gyroscope based on dual-polarization configuration_is designed and realized. The 24-hour stability test shows aself-noise level of 3 × 10−9 rad/s/√Hz within the frequency range of 0.001Hz to 1Hz. &... 详细信息

ISBN: (纸本)9781957171005

关键词： Gyroscopes

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