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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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Capped L2p-Norm based 2DPCA with Adaptive Capped Threshold Learning for image Processing 23

Capped L2p-Norm Based 2DPCA with Adaptive Capped Threshold L...

引用

23rd IEEE international conference on Communication technology, ICCT 2023

作者： Liu, Meiling Feng, Wei Pei, Chengquan Wang, Qianqian Gao, Quanxue School of Telecommunications Engineering Xidian University Xi'an China School of Computer Science and Technology Xi'an Jiaotong University Xi'an China School of Artificial Intelligence Xidian University Xi'an China

ISBN: (纸本)9798350325959

Two-dimensional principal component analysis (2DPCA) is an effective technique to extract low-dimensional representations for face clustering and recognition. However, it suffers from extreme sensitivity to outliers and noise. To improve the robustness of 2DPCA, we design a novel optimal-mean 2DPCA with adaptive capped L2p-norm minimization, called Adaptive Capped L2p-2DPCA, which adopts capped L2p-norm in the objective function to measure the reconstruction error. Simultaneously, Adaptive Capped L2p-2DPCA integrates the adaptive capped threshold learning during the optimization process, such that the capped threshold can be obtained without human intervention. Furthermore, we develop a non-greedy iterative algorithm to solve Adaptive Capped L2p-2DPCA. The proposed algorithm has a closed-form solution in each iteration and is proven to achieve good convergence. We conduct experiments on four face image datasets, and the recognition rates on the four datasets Extended Yale B, AR, CMU PIE, and ORL are 5.02%, 1.86%, 0.47%, and 5.5% higher than the second best method, respectively, which indicates the effectiveness and superiority of our method. © 2023 IEEE.

关键词： 2DPCA adaptive capped learning capped L2p-norm

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Cognitive Architecture based Spectrum Sharing between 4G LTE-Advanced Network and TV Band

Cognitive Architecture Based Spectrum Sharing between 4G LTE...

引用

international conference on Advanced Technologies for signal and image Processing (ATSIP)

作者： Hashim Elshafie Naoufel Kraiem Rashid A. Saeed K Saleem A Shahid Khan Mosab Hamdan College of Computer Science King Khalid University Al Farah Abha Saudi Arabia College of Computers and Information Technology(CIT) Taif University Taif Saudi Arabia Center of Excellence in Information Assurance (CoEIA) King Saud University Riyadh Saudi Arabia Faculty of Computer Science and IT Universiti Malaysia Sarawak Kota Samarahan Sarawak Malaysia Walton Institute for Information and Communication Systems Science South East Technological University Waterford Ireland

ISBN: (数字)9798350351484

ISBN: (纸本)9798350351491

There is now a barrier in place because to the exponential increase in demand for faster wireless communications to meet the needs of more applications. There are almost no remaining frequency bands to allot for new systems since the spectral resources are running low. based on a geographic TV database, this article presents the prospective approach sharing concerns between LTE-Advanced and TV band. The enabling technology will work with LTE-Advanced devices to address the TV band’s under used

关键词： Wireless communication TV Databases image processing White spaces Long Term Evolution

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Performance Testbed in IoT Network based on ZigBee and NB-IoT Technologies

Performance Testbed in IoT Network Based on ZigBee and NB-Io...

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international Technical conference o Circuits/systems, Computers and Communications (ITC-CSCC)

作者： Tanakorn Inthasuth Watthanakorn Choterungrote Chatdanai Bandasak Thanawut Banboon Ngoc Thien le Department of Telecommunication Engineering Faculty of Engineering Rajamangala University of Technology Srivijaya Songkhla Thailand Department of Urban Engineering University of Architecture Ho Chi Minh City Ho Chi Minh City Vietnam

ISBN: (数字)9798350379051

ISBN: (纸本)9798350379068

The inter-protocol communication system acts as an interface and is the link where problems of communication may occur. This paper is dedicated to exploring wireless communication through the ZigBee system, which offers short-range communication and supports mesh networks. ZigBee plays a pivotal role in wireless sensor network (WSN) and their related applications. Nevertheless, the WSN can be linked to the internet system through several approaches, but this study focuses on the connection through a gateway (GW) using Narrowband internet of Things (NB-IoT) technology, which is particular to the IoT system. The GW testing has been performed to measure the data transfer rate and received signal strength indicator (RSSI) for detecting the limits of the system. Our WSN consisted of 8 nodes and this was more than twice the number of the XBee buffer that was capable of receiving packets simultaneously. In addition, GW devices have been installed in the different types of enclosures to determine the signal levels for future real installation guidelines.

关键词： Wireless communication Performance evaluation Wireless sensor networks Transmitters Zigbee Received signal strength indicator internet of Things

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Research on Electrical Safety Monitoring System based on Narrow-Band internet of Things 4

Research on Electrical Safety Monitoring System Based on Nar...

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4th international conference on Intelligent Control, Measurement and signal Processing, ICMSP 2022

作者： Xue, Zhao-Mei Qiu, Xi-Rui Zhao, Zhi-Feng Gao, Xu School of Electronic Engineering Xi'an Shiyou University Xi'an China

ISBN: (数字)9781665486583

ISBN: (纸本)9781665486583

Because of the national attention to fire safety, the fire protection industry has developed rapidly. As an important part of fire safety, electrical safety monitoring system has always occupied an important position in the field of safety supervision. Due to the increasing material and cultural needs of the people, the system has higher requirements for network convenience, data accuracy and transmission stability. Therefore, the traditional electrical fire monitoring equipment uses wired equipment to collect information, which has the disadvantages of easy aging, high power consumption and low sensitivity. At the same time, for Zigbee, Wi-Fi, Bluetooth and other wireless technology networking acquisition systems, there are also shortcomings such as limited network transmission data and difficult remote mass data storage. Using the internet of Things technology, a hardware and software system for electrical safety monitoring is designed. The system mainly includes STM32 processor and corresponding modules, which are responsible for collecting the current, voltage and temperature information of the measured circuit. The data are transmitted to the cloud platform server through the NB-IoT communication module, and the data information is received in real time by the mobile phone terminal, and the detector is remotely controlled. Through the actual test, the system collects data accurately, and the cloud platform storage is convenient for remote access, which has certain application value. © 2022 IEEE.

关键词： internet of things

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Research on Synchronization Method of Coherent Microwave Frequency Hopping Communication

Research on Synchronization Method of Coherent Microwave Fre...

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international conference on Microwave and Millimeter Wave technology Proceedings

作者： Yang Liu Xiang Wu Fan Yang Feiliang Chen Hao Jiang Mo Li Jian Zhang University of Electronic Science and Technology of China Chengdu China

ISBN: (数字)9798350389968

ISBN: (纸本)9798350389975

Aiming at the problems of complex architecture, poor acquisition accuracy and long establishment time of traditional synchronization method in frequency-hopping systems, a self-synchronization method based on edge detection is introduced in this paper. The wideband FH signal is de-hopped to the intermediate frequency signal by image frequency rejection receiver. The influence of ambient temperature drift is eliminated by using two-channel differential sampling. Then, the rising edge of the envelope signal is accurately identified and tracked to realize fast synchronization of the received hopping signal. Finally, the feasibility and effectiveness of the proposed method are verified through a Ku-band frequency hopping system.

关键词： Tracking loops Time-frequency analysis Accuracy image edge detection Millimeter wave technology Spread spectrum communication Receivers

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VulSAT: Source Code Vulnerability Detection Scheme based on SAT Structure

VulSAT: Source Code Vulnerability Detection Scheme Based on ...

引用

IEEE international conference on signal and image Processing (ICSIP)

作者： Jintao Xue Zihan Yu Yubo Song Zhongyuan Qin Xin Sun Wen Wang School of Cyber Science and Engineering Southeast University Nanjing China Internet Technology Center State Grid Zhejiang Electric Power Co. Ltd. Research Institute Hangzhou China Internet Department State Grid Zhejiang Electric Power Co. Ltd Hangzhou China

The number of software vulnerabilities have increased rapidly, and their forms have shown the characteristics of complexity and diversity, which has brought severe challenges to software systems. Deep learning can automatically learn the features of code and is widely used in source code vulnerability detection. Some studies treat codes as text sequences, ignoring the structural relationship between lines of code. Other studies extract the code as a graph structure, but ignore the order relationship of code lines and do not make full use of the dependencies between code lines. This paper proposes a C/C++ source code vulnerability detection scheme based on SAT (Structure-Aware Transformer) structure. It first standardizes the source code, then extracts the PDG (program dependency graph) representation of source code, next convert each node into a vector representation using sentence embedding, which retains the dependencies between nodes. Finally input it into the SAT architecture model for training, and judge whether the input program contains vulnerabilities according to the output results. We compared VulSAT with a variety of vulnerability detection methods (i.e., Devign, SySeVR, VulCNN, Checkmarx, VulDeePecker), and selected C/C++ functions in the SARD vulnerability dataset as experimental objects. The performance of accuracy rate and false positive rate has been improved to a certain extent.

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A Deep Learning-based Methodology for Detecting and Visualizing Continuous Gravitational Waves 19th

A Deep Learning-Based Methodology for Detecting and Visualiz...

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19th international conference on Artificial Intelligence Applications and Innovations (AIAI)

作者： Pintelas, Emmanuel Livieris, Ioannis E. Pintelas, Panagiotis Univ Patras Dept Math Patras Greece

ISBN: (纸本)9783031341137;9783031341113;9783031341106

Since the Gravitational Waves' initial direct detection, a veil of mystery from the Universe has been lifted, ushering a new era of intriguing physics, astronomy, and astrophysics research. Unfortunately, since then, not much progress has been reported, because so far all of the detected Gravitational Waves fell only into the Binary bursting wave type (B-GWs), which are created via spinning binary compact objects such as black holes. Nowadays, as-tronomy scientists seek to detect a new type of gravitational waves called: Continuous Gravitational Waves (C-GWs). Unlike the complicated burst na-ture of B-GWs, C-GWs have elegant and much simpler form, being able to provide higher quality of information for the Universe exploration. Never-theless, C-GWs are much weaker comparing to the B-GWs, which makes them considerably harder to be detected. For this task, we propose a novel Deep-Learning-based methodology, being sensitive enough for detecting and visualizing C-GWs, based on Short-Time-Fourier data provided by LIGO. based on extensive experimental simulations, our approach significantly outperformed the state-of-the-art approaches, for every applied experimental configuration, revealing the efficiency of the proposed methodology. Our expectation is that this work can potentially assist scientists to improve their detection sensitivity, leading to new Astrophysical discoveries, via the incor-poration of Data-Mining and Deep-Learning sciences.

关键词： Deep learning 2D image processing SFT signal processing remote sensing applications ML methods for sensing systems

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Enabling Effective Low-Light Perception using Ubiquitous Low-Cost Visible-Light Cameras 22

Enabling Effective Low-Light Perception using Ubiquitous Low...

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30th ACM international conference on Multimedia (MM)

作者： Morawski, Igor Natl Taiwan Univ Taipei Taiwan

ISBN: (纸本)9781450392037

Deep ConvNets have changed and improved the capabilities and robustness of machine perception models such as object detectors. Meanwhile, visual perception using visible-light sensors under low-light conditions is still challenging for deep learning models. While there are sensors that allow mitigating some of the limitations of visible-light cameras, they are often infeasible in real-life cost-, power- or space-constrained systems. By contrast, to extend the functionality of existing vision systems based on visible-light cameras, we investigate effective machine perception in low light using these ubiquitous low-cost sensors. Our first contribution to the computer vision community was our high-quality object detection dataset targeting low-light machine perception. Next, we proposed a neural image signal Processor that processes raw sensor data into representation optimal for low-light machine cognition. In the future work, we aim to focus on a higher-level approach to low-light machine cognition. Finally, we plan to address low-light conditions holistically by integrating low- and high-level domain solutions in a common framework.

关键词： low light machine perception object detection ISP image enhancement image restoration low-light enhancement

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image Processing and Visualization technology Application of an Improved Deep Learning Algorithm

Image Processing and Visualization Technology Application of...

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Network, Multimedia and Information technology (NMITCON) international conference on

作者： Yunsheng Deng Yinghui Huang Zhangbao Chen Yan Chen Bengbu University Bengbu Huainan City Anhui China

ISBN: (数字)9798350372892

ISBN: (纸本)9798350372908

In today’s world, technology is changing our way of life and work at an alarming rate. This paper studies the performance of an improved deep learning algorithm in image processing tasks, introduces the implementation principle of algorithm design, and puts forward an improved deep learning algorithm. In the experimental method part, a group of experiments are designed to evaluate the image quality performance of the improved deep learning algorithm, which is based on three key performance indicators: Peak signal-to-Noise Ratio (PSNR), Interactive Response Time (IRT) and Structural Similarity Index Measure (SSIM). The research conclusion shows that the peak signal-to-noise ratio (PSNR) of the improved image quality-preserving deep learning algorithm is as high as 58 dB. The maximum IRT measurement of the improved algorithm is only 95 ms, which provides users with faster response speed and enables users to experience a smoother interactive experience in real-time image processing applications.

关键词： Deep learning image quality Visualization PSNR image processing Scalability Real-time systems Time measurement Robustness Time factors

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Smart City Management based Data applications using Improved Seagull Optimization algorithm with Dense Net 121

Smart City Management based Data applications using Improved...

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Distributed systems, Computer Networks and Cybersecurity (ICDSCNC), international conference on

作者： Tong Liu Haifei Lu Shenyang Jianzhu Unversity Shenyang China College of Urban Construction Zhejiang Shuren University Hangzhou China

ISBN: (数字)9798350375442

ISBN: (纸本)9798350375459

Recently, rapid growth of information technology, has progressively entered the daily life of combinations. Smart city management is the innovative technology by combining internet of Things (IoT), cloud computing and mobile internet technologies to achieve modern living experience. By analyzing the current situation of smart city this research presented Improved Seagull Optimization Algorithm with Dense Net -121 (ISOA-Dense Net-121) to improve processes in digitalization economy. The suggested model involves sensor-integrated systems to optimize by generating accurate predictions. ISOA is utilized to simulate the seagull migration for global exploration, resulting in better weight initialization. Then, DenseNet-121 utilized to improve the performance in difficult image recognition tasks. By removing the unnecessary data applications, these hybridized model ISOA-DenseNet-121 reduce the environmental effects in SWM. According to the result it illustrated that when compared to existing models such as ResNeXt, SWM and Smart Waste Bin Management System (SWBMS) the proposed ISOA-Dense Net-121 recommended strategy outperformed the others in terms of accuracy, f-score of 99.3%, precision of 99.4% and recall of 99.2%.

关键词： Cloud computing Accuracy image recognition Smart cities Computational modeling Predictive models Big Data applications Data models internet of Things Optimization

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