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检索条件"任意字段=International Conference on Signal Image Technology and Internet Based Systems"

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Multi-DSP Joint SAR Real-Time Imaging System based on PFA Sub-Aperture Imaging Algorithm 2

Multi-DSP Joint SAR Real-Time Imaging System Based on PFA Su...

引用

2nd IEEE international conference on signal, Information and Data Processing, ICSIDP 2024

作者： Liu, Xueqing Song, Yue Li, Zhongyu Wu, Junjie Yang, Jianyu Du, Ping Zhang, Yueyue Dong, Mingji Miao, Xin Liu, Jiaxuan University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu China Shanghai Satellite Network Research Institute Co. Ltd. Shanghai Key Laboratory of Satellite Network Shanghai China

ISBN: (纸本)9798331515669

The Synthetic Aperture Radar(SAR) real-time imaging system designed with multi-DSP architecture has been widely used in both airborne and satellite platforms. In the context of real-time imaging systems, Polar Format Algorithm(PFA) fall short of meeting the system's real-time demands. This paper proposes a multi DSP architecture SAR imaging system based on sub-aperture PFA to meet the real-time imaging requirements. The system utilizes multiple sub-aperture echo data to design a "2+1"DSP C6678 hardware architecture, and implements the sub aperture PFA algorithm in parallel on the hardware to improve imaging efficiency. Furthermore, we performed phase gradient autofocus processing on the imaging results and achieved high-resolution images. The experimental results show that compared with traditional PFA, the proposed sub aperture PFA algorithm and hardware architecture reduce imaging time by 54%. © 2024 IEEE.

关键词： image enhancement

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A Comparative Analysis of Switched Gate Implementations in Wallace Tree Multipliers 3

A Comparative Analysis of Switched Gate Implementations in W...

引用

3rd international conference on Artificial Intelligence For internet of Things, AIIoT 2024

作者： Pallati, Rama Rohith Bandi, Neeraja Chandra Sekhar, E. Ravikanti, Swetha Chaitanya Bharathi Institute of Technology Department of ECE Hyderabad India Dayananda SagarCollege of Engineering Department of ETE Bangalore India

ISBN: (纸本)9798350372120

Binary multipliers are used in microprocessors, digital signal processors, and various digital systems for efficient computation of binary arithmetic operations. Wallace Tree multiplier is used over others because it can perform high-speed, area-efficient, scalable, and power-efficient multiplication in many digital systems and applications. This paper aims to design an optimized 3x3 Wallace Tree multiplier using switched gate circuits such as transmission gates and Pass transistor logic gates in Cadence Virtuoso 45nm technology. Using switched gates, the logic levels required to perform the summation can be decreased. A comparative analysis has been carried out for the designed Wallace tree multiplier circuits and output results based on the PTL logic are showing better results in terms of area and power compared to the conventional model © 2024 IEEE.

关键词： Digital signal processors

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image-based Feature Representation for Enhanced Cyber-Attack Detection in IoHT Environments 1

Image-based Feature Representation for Enhanced Cyber-Attack...

引用

1st international conference on Emerging Technologies for Dependable internet of Things, ICETI 2024

作者： Al-Azzani, Abdoualwase M. Al-Shalabi, Ahmed Abdullah Ghurab, Mossa Alhrazi, Firdaus Alhomdy, Sharaf A. Algabri, Malek Department of Computer Science Sana’a University Sana’a Yemen Department of Information Technology Sana’a University Sana’a Yemen

ISBN: (纸本)9798331533557

The complexity of cybersecurity risks has expanded dramatically with the fast expansion of the internet of Health Things (IoHT), especially with regard to cyberattacks that target healthcare systems. In healthcare settings, data privacy and integrity are very important, hence developing improved detection techniques that can reliably identify fraudulent activity is urgently needed. In order to improve cyber-attack detection in IoHT, this research presents an image-based feature representation technique that makes use of convolutional neural networks (CNNs), notably the MobileNet architecture. With the use of the ECU-IoHT dataset’s network traffic statistics, the suggested model is able to catch intricate patterns that point to infiltration. Because MobileNet-CNN computation is efficient, it can be deployed in real-time in low-resource situations, which are typical of IoHT installations. Our method outperforms current state-of-the-art methods, with lower false positive and negative rates and better classification accuracy of 99.1%, precision of 99.00%, recall of 97.1%, and F1-score of 98.4%. The findings highlight how image-based deep learning models may improve cybersecurity safeguards in internet of Things frameworks by offering a powerful instrument for proactive threat identification and removal. This study lays the groundwork for future studies that will use image-based representations of features for real-time threat identification, furthering the area of IoHT cybersecurity. © 2024 IEEE.

关键词： Cyber attacks

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Deep Learning-based Method for 5G Micro-Base Station signal Identification 5

Deep Learning-Based Method for 5G Micro-Base Station Signal ...

引用

5th IEEE international conference on Power, Intelligent Computing and systems, ICPICS 2023

作者： Haojie, Jiang Qiuyu, Luo Yuan, Wang Xianghua, An Lanzhou University of Technology Lanzhou China

ISBN: (纸本)9798350333442

The State Council's latest Guidance on Actively Promoting 'internet +' emphasizes that 'the development of a new generation of mobile communication networks and the next generation of the internet should be accelerated', and the construction of 5G base stations has become a top priority in this new era. However, the current 5G signal has problems such as high coverage duplication rate. This paper proposes an intelligent 5G micro-base station signal identification method based on deep learning. Combining infrared imaging technology and machine learning technology, the deep learning algorithm can effectively reduce the duplicated coverage and the number of base stations installed in some areas, so as to reduce the waste of power caused by the idle power consumption of base stations and enhance the 5G signal strength. © 2023 IEEE.

关键词： Deep learning

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Trust based Cooperative Secure Routing Protocols for internet of Things (IoT) 2

Trust Based Cooperative Secure Routing Protocols for Interne...

引用

2nd international conference on Recent Trends in Microelectronics, Automation, Computing, and Communications systems, ICMACC 2024

作者： Mekala, Sagar Ramji, Bhukya CVR College of Engineering Dept. of Computer Science and Engineering Hyderabad India Kakatiya Institute of Technology and Science Dept. of Computer Science and Engineering Hanmakonda India

ISBN: (纸本)9798350366570

The internet of Things has rapidly emerged and continues to create services, software, sensors-embedded devices, and protocols. IoT allows physical objects to communicate, exchange information, and make decisions while performing critical jobs. The internet of Things is enhanced by wireless sensor networks, which serve as a continuous layer. To gain adoption and spread, internet of things-based sensor networks must overcome serious general and specialized risks and technological hurdles. The main drawbacks of wireless sensor networks are insufficient resources. internet of Things (IOT)-based Wireless Sensor Networks have issues in energy consumption, longevity, throughput, routing, and security. The goal of this effort was to enhance network longevity, throughput, packet latency/loss, and better encounters with hostile nodes. Consider wireless energy harvesting in the proposed three-layer cluster-based wireless sensor network routing protocol to enhance network lifespan. The proposed approach is a Trust based Cooperative Secure Routing Protocol (TCSRP) technique with security system to obtain malicious activities of objects and to slant them into blacklist. Finally, experiments were done to test the methodology. It outperforms most traditional routing protocols like AODV, DSR, and DSDV. © 2024 IEEE.

关键词： Network layers

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Innovative deep learning and signal processing methods for ECG abnormality detection and diagnosis 4

Innovative deep learning and signal processing methods for E...

引用

4th international conference on Green Communication, Network, and internet of Things, CNIoT 2024

作者： Liu, Yuan Ma, Jitong College of International Collaboration Dalian Maritime University Dalian116000 China Information and Technology College Dalian Maritime University Dalian116000 China

ISBN: (纸本)9781510685710

With the advancement of medical technology, electrocardiogram (ECG) monitoring plays a crucial role in the diagnosis of heart diseases. However, traditional ECG analysis methods rely on the subjective judgment of professional doctors, which has certain limitations. This paper proposes a technology for the detection and diagnosis of ECG abnormalities based on deep learning and signal processing, aiming to enhance the automation and accuracy of ECG signal analysis. Initially, this paper employs wavelet transforms for preprocessing of ECG signals, effectively removing noise while preserving key ECG features. Subsequently, Recurrent Neural Networks (RNNs), specifically Long Short-Term Memory networks (LSTM), are utilized for time-series analysis of ECG signals to differentiate between normal and abnormal ECG signals. Furthermore, a Convolutional Neural Network (CNN) is constructed to extract features from abnormal ECG signals for the identification of specific types of abnormalities. To augment the model's feature expression capability, this paper also introduces an attention mechanism, which enhances the weight of key signal segments, thereby improving the accuracy of abnormality detection. Experimental results demonstrate that this method achieves a high accuracy rate in the task of ECG abnormality detection, effectively assisting doctors in the diagnosis of electrocardiograms. This research not only has potential application value in intelligent monitoring systems and data mining technology but also provides a new technological approach for the automated diagnosis of electrocardiograms, with prospects for playing a significant role in the fields of industrial internet of Things and intelligent manufacturing. © 2024 SPIE.

关键词： Long short-term memory

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A remote sensing image de-noising method based on wavelet packet decomposition and information entropy threshold function

A remote sensing image de-noising method based on wavelet pa...

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2024 international conference on image, signal Processing, and Pattern Recognition, ISPP 2024

作者： Ma, Hongjin Zhao, Jiayu Zhang, Weiwei School of Science Xi'an University of Architecture and Technology Shaanxi Xi'an710055 China School of Mathematics and Statistics Northwestern Polytechnical University Shaanxi Xi'an710072 China

ISBN: (纸本)9781510680425

Remote sensing images are widely used in various fields, such as geographic information systems, environmental monitoring, and agricultural management. However, remote sensing images are often corrupted by various noises during acquisition, transmission, and storage, which degrade the image quality and affect the image analysis and utilization. Therefore, de-noising remote sensing images is an important step to improve the image quality and application performance. In this paper, we propose a remote sensing image de-noising method based on wavelet packet decomposition and information entropy threshold function. The proposed method uses wavelet packet decomposition to perform multi-resolution analysis on remote sensing images, and combines information entropy threshold function to adaptively suppress noises. The experimental results show that the proposed method can effectively remove Gaussian noise and salt-and-pepper noise, and preserve the edge and detail information of remote sensing images. The proposed method outperforms the existing methods in terms of peak signal-to-noise ratio, structural similarity index, and visual quality. © 2024 SPIE.

关键词： Wavelet decomposition

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Agricultural IoT PDRR scheme based on an improved cyber kill chain

Agricultural IoT PDRR scheme based on an improved cyber kill...

引用

2024 international conference on signal Processing and Communication Security, ICSPCS 2024

作者： Huang, Rikun Ma, Rong Zhang, Hao School of Machinery and Transportation Southwest Forestry University Yunnan Kunming650224 China Hangzhou Lingxin Mathematical Information Technology Co. Ltd. Zhejiang Hangzhou310000 China School of Computer Science and Technology Shenyang University of Chemical Technology Liaoning Shenyang110142 China

ISBN: (纸本)9781510681699

As the application of internet of Things (IoT) technology in agriculture deepens, the lack of security in agricultural IoT systems has become one of the main bottlenecks restricting the development of agricultural IoT. To address the data and system security issues of agricultural IoT, this paper proposes an agricultural IoT PDRR scheme based on an improved cyber kill chain. By understanding the lifecycle of network attacks through the improved four-step cyber kill chain model, and utilizing the synergistic effects of honeypot and firewall technologies, a defense system capable of adapting to attacker behaviors and effectively disrupting the cyber kill chain is constructed. The PDRR is achieved by combining proactive and passive defense methods. Experimental results show that the agricultural IoT PDRR scheme based on the improved cyber kill chain proposed in this paper can effectively interfere with and disrupt the cyber kill chain. Moreover, compared to traditional defense methods, this scheme demonstrates significant advantages in recognizing unknown attack patterns and acquiring attack intelligence. © 2024 SPIE.

关键词： internet of things

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internet of Vehicles and Digital Twin Framework for Unmanned Tracked Vehicles based on 5G Communication

Internet of Vehicles and Digital Twin Framework for Unmanned...

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2022 international conference on signal Processing and Communication technology, SPCT 2022

作者： Wang, Jiangfeng Chen, Wei Weapons and Control Department Army Academy of Armed Force Beijing China Vehicle Engineering Department Army Academy of Armed Force Beijing China

ISBN: (纸本)9781510664333

This paper briefly introduces the internet of Vehicles, 5G communication and digital twins. Aiming at the driverless tracked vehicle group developed in the earlier stage, combined with vehicle network and 5G communication, a 5G communication based vehicle networking framework for driverless tracked vehicle group is proposed. On the basis of 5G communication based unmanned tracked vehicle group internet of Vehicles framework, combined with digital twins, the digital twin framework of unmanned tracked vehicle group is proposed at two levels, and comparative analysis experiments are carried out. © 2023 SPIE.

关键词： 5G mobile communication systems

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image Dehazing Scheme based on Haze-line and DCP Prior 6

Image Dehazing Scheme Based on Haze-line and DCP Prior

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6th international conference on internet of Things, Automation and Artificial Intelligence, IoTAAI 2024

作者： Wu, Xinchun Wang, Xiao Huang, Xiaobing Zhang, Xiaojun Ju, Zhaoyang Southwest Jiaotong University School of Information Science and Technology Chengdu610097 China Technology Co. Ltd Chengdu610095 China

ISBN: (纸本)9798350386974

In visual research, researchers strive to understand how optical sensors capture image information and how the brain interprets and processes this information. However, natural atmospheric haze introduces serious visual challenges in images. Haze causes loss of image details, color distortion, and blurring of depth information, posing a significant challenge for many intelligent device applications. This paper combines the strengths of the Haze-line and DCP algorithms, complementing their weaknesses, to develop a method that accurately restores detailed object information in hazy images without introducing distortion or artifacts. By constraining atmospheric light, the method aims to approximate the true atmospheric light value for each pixel in the image. It involves solving the transmission twice and imposing constraints to maximize the restoration of transmission values, which often deviate significantly from real transmission rates due to differences in depth of field. Peak signal-to-noise ratio and structural similarity are used to evaluate the dehazing performance. Experimental results demonstrate that compared to other algorithms, this approach achieves effective dehazing with restored detail while minimizing distortion in the resulting hazefree images. © 2024 IEEE.

关键词： Restoration

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