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2024 International Conference on Image, Signal Processing, and Pattern Recognition, ISPP 2024

作者： He, Xin Zhu, Wenzhong Liu, Yu Li, Jie School of Computer Science & Engineering Sichuan University of Science & Engineering Yibin China

ISBN: (纸本)9781510680425

To address the challenges of low detection accuracy and substantial model parameter size present in traditional safety helmet detection algorithms, this study introduces an enhanced algorithm known as P2DFE-YOLOv8n, specifically crafted for the detection of safety helmet *** algorithm builds upon the foundation of YOLOv8n by incorporating a specialized detection head for small targets, aimed at improving the accuracy of safety helmet ***, it eliminates the detection head for large targets to reduce the model's parameter count and computational complexity, without compromising detection *** inclusion of the FasterNet Block and C2f modules in the model architecture serves to further streamline the model and enhance its ***, the employment of the EMA (Efficient Multi-Scale Attention) attention mechanism within the neck networks allows for focused processing of crucial information related to the individual wearing the helmet, thereby significantly increasing detection *** evaluations conducted on the proprietary H-helmet safety gear database demonstrate that the refined P2DFE-YOLOv8n algorithm achieves an mAP@0.5 score of 92.3%, with a remarkably reduced parameter volume of just *** to the original YOLOv8n model, the refined algorithm presents a reduction in parameter size and model size by 2.25M (74.8%) and 4.294MB (70.6%), ***, the enhanced model showcases improvements in accuracy, recall rate, mAP@0.5, mAP@0.5:0.95, and FPS by 1.8%, 0.2%, 1.0%, 0.2%, and 14, respectively, underscoring the efficacy of the proposed modifications in optimizing both performance and efficiency in safety helmet detection tasks. © 2024 SPIE.

关键词： Safety devices

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Identify information sources with different start times in complex networks based on sparse observers

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Chinese Physics B 2024年第11期33卷 467-479页

作者： Yuan-Zhang Deng Zhao-Long Hu Feilong Lin Chang-Bing Tang Hui Wang Yi-Zhen Huang School of Computer Science and Technology Zhejiang Normal UniversityJinhua 321004China School of Physics and Electronic Information Engineering Zhejiang Normal UniversityJinhua 321004China School of Information Engineering Jinhua PolytechnicJinhua 321016China

The dissemination of information across various locations is an ubiquitous occurrence,however,prevalent methodologies for multi-source identification frequently overlook the fact that sources may initiate dissemination at distinct initial *** there are many research results of multi-source identification,the challenge of locating sources with varying initiation times using a limited subset of observational nodes remains *** this study,we provide the backward spread tree theorem and source centrality theorem,and develop a backward spread centrality algorithm to identify all the information sources that trigger the spread at different start *** proposed algorithm does not require prior knowledge of the number of sources,however,it can estimate both the initial spread moment and the spread *** core concept of this algorithm involves inferring suspected sources through source centrality theorem and locating the source from the suspected sources with linear *** experiments from synthetic and real network simulation corroborate the superiority of our method in terms of both efficacy and ***,we find that our method maintains robustness irrespective of the number of sources and the average degree of *** with classical and state-of-the art source identification methods,our method generally improves the AUROC value by 0.1 to 0.2.

关键词： complex networks information spread source identification backward spread centricity

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IM-EDRD from Retinal Fundus Images Using Multi-Level Classification Techniques

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Intelligent Automation & Soft Computing 2023年第1期35卷 567-580页

作者： M.P.Karthikeyan E.A.Mary Anita Department of Computer Science and Engineering R.M.K.Engineering CollegeChennai601206India Department of Computer Science and Engineering School of Engineering and TechnologyChrist UniversityBengaluru560029India

In recent years,there has been a significant increase in the number of people suffering from eye illnesses,which should be treated as soon as possible in order to avoid *** Fundus images are employed for this purpose,as well as for analysing eye abnormalities and diagnosing eye *** can be recognised as bright lesions in fundus pictures,which can be thefirst indicator of diabetic *** that in mind,the purpose of this work is to create an Integrated Model for Exudate and Diabetic Retinopathy Diagnosis(IM-EDRD)with multi-level *** model uses Support Vector Machine(SVM)-based classification to separate normal and abnormal fundus images at thefirst *** input pictures for SVM are pre-processed with Green Channel Extraction and the retrieved features are based on Gray Level Co-occurrence Matrix(GLCM).Furthermore,the presence of Exudate and Diabetic Retinopathy(DR)in fundus images is detected using the Adaptive Neuro Fuzzy Inference System(ANFIS)classifier at the second level of *** detection,blood vessel extraction,and Optic Disc(OD)detection are all processed to achieve suitable ***,the second level processing comprises Morphological Component Analysis(MCA)based image enhancement and object segmentation processes,as well as feature extraction for training the ANFIS classifier,to reliably diagnose ***,thefindings reveal that the proposed model surpasses existing models in terms of accuracy,time efficiency,and precision rate with the lowest possible error rate.

关键词： Retinal fundus images exudate diabetic retinopathy SVM ANFIS morphological component analysis

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Classification Methoed of Cement Concrete Pavement Conditions Based on Improved EfficientNet 4

Classification Methoed of Cement Concrete Pavement Condition...

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4th International Conference on Artificial Intelligence, Virtual Reality and Visualization, AIVRV 2024

作者： Li, Jie Zhu, Wenzhong Liu, Yu Zhang, Zhike School of Computer Science & Engineering Sichuan University of Science & Engineering Yibin China

ISBN: (纸本)9798331528744

Given the drawback of high complexity and low recognition rate of the existing cement concrete pavement state classification models and methods, this paper proposes an improved model based on EfficientNet for the classification of cement concrete pavement states in five cases. A more comprehensive and effective feature extraction ability for the model is provided by an attention module for the performance of convolutional neural networks introduced in the model. To reduce the model complexity, an efficient channel attention module is introduced. The improved network model has higher detection accuracy and better adapts to the classification of cement concrete pavement states. The image samples come from the open-source dataset (Road Surface Classification Dataset, RSCD). Through reclassification, a total of 58,568 images of five types of cement concrete pavements in different weather conditions are established as the dataset to train the proposed model and obtain the classification results of cement concrete pavement images. The experimental results show that the accuracy of the proposed model on the dataset reaches 95.57%, which is better than other comparison models and can accurately and effectively classify the cement concrete pavement states under different conditions. © 2024 IEEE.

关键词： Convolutional neural networks

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Time-of-Use Price Resource Scheduling in Multiplex Networked Industrial Chains

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Tsinghua science and Technology 2025年第1期30卷 303-317页

作者： Pan Li Kai Di Xinlei Bai Fulin Chen Yuanshuang Jiang Xiping Fu Yichuan Jiang School of Cyber Science and Engineering Southeast UniversityNanjing 211189China School of Computer Science and Engineering Southeast UniversityNanjing 211189China PredictHQ Ltd. Auckland 1010New Zealand

With the advancement of electronic information technology and the growth of the intelligent industry,the industrial sector has undergone a shift from simplex,linear,and vertical chains to complex,multi-level,and multi-dimensional networked industrial *** order to enhance energy efficiency in multiplex networked industrial chains under time-of-use price,a coarse time granularity task scheduling approach has been *** approach adjusts the distribution of electricity supply based on task deadlines,dividing it into longer periods to facilitate batch access to task ***,traditional simplex-network task assignment optimization methods are unable to achieve a globally optimal solution for cross-layer links in multiplex networked industrial *** solutions struggle to balance execution costs and completion efficiency in time-of-use price ***,this paper presents a mixed-integer linear programming model for solving the problem scenario and two algorithms:an exact algorithm based on the branch-and-bound method and a multi-objective heuristic algorithm based on cross-layer policy *** algorithms are designed to adapt to small-scale and large-scale problem scenarios under coarse time *** extensive simulation experiments and theoretical analysis,the proposed methods effectively optimize the energy and time costs associated with the task execution.

关键词： multiplex networked industrial chains resource scheduling time-of-use price

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A Lowcost UAV Task Offloading Scheme based on Trustable and Trackable Data Routing

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2023年第9期9卷 1-16页

作者： Bai, Jing Gui, Jinsong Huang, Guosheng Dong, Mianxiong Wang, Tian Zhang, Shaobo Liu, Anfeng School of Computer Science and Engineering Central South University Changsha China School of Information Science and Engineering Hunan First Normal University Changsha China School of Computer Science and Engineering Muroran Institute of Technology Japan Artificial Intelligence and Future Networks Beijing Normal University & UIC Zhuhai China School of Computer Science and Engineering Hunan University of Science and Technology Xiangtan China

As a promising edge computing paradigm, task offloading involves transferring data from resource-limited devices to high-performance servers to expedite processing. However, devices in isolated networks without direct Internet connections face challenges in task offloading. To address this issue, we propose a novel Low-cost Unmanned Aerial Vehicle (UAV) Task Offloading Scheme based on Trustable and Trackable Data Routing (LTOTT) for deadline-aware tasks in non-connected networks. The main contributions of LTOTT are as follows: (1) A novel dissemination method that devices route different numbers of Copied Tasks (CTs) and Task Computing Notices (TCNs) in different directions based on task deadlines is proposed to enable the UAV to get tasks earlier and complete them in time. (2) In order to reduce the risk of malicious attacks during the spreading of CTs and TCNs, a trust evaluation based on a trackable data routing method is proposed to ensure secure transmission. (3) In addition, based on the evaluated trust and the received information, a dynamic UAV flight trajectory optimization is proposed to enable tasks completed before their deadlines. A large number of experimental results show that LTOTT increases the task completion rate by 41.41% - 134.15%;reduces average delay and UAV's flight distance respectively by 26.88% - 51.52%, 16.37% -73.40% compared with the existing schemes. IEEE

关键词： Antennas

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Orbit-Orbit Interaction in Spatiotemporal Optical Vortex

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engineering 2025年第2期45卷 44-51页

作者： Jian Chen Jie Zhao Xi Shen Dewei Mo Cheng-Wei Qiu Qiwen Zhan School of Optical-Electrical and Computer Engineering University of Shanghai for Science and TechnologyShanghai 200093China Shanghai Key Laboratory of Modern Optical System University of Shanghai for Science and TechnologyShanghai 200093China Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore

While spin-orbit interaction has been extensively studied,few investigations have reported on the interaction between orbital angular momenta(OAMs).In this work,we study a new type of orbit-orbit coupling between the longitudinal OAM and the transverse OAM carried by a three-dimensional(3D)spatiotemporal optical vortex(STOV)in the process of tight *** 3D STOV possesses orthogonal OAMs in the x-y,t-x,and y-t planes,and is preconditioned to overcome the spatiotemporal astigmatism effect.x,y,and t are the axes in the spatiotemporal *** corresponding focused wavepacket is calculated by employing the Debye diffraction theory,showing that a phase singularity ring is generated by the interactions among the transverse and longitudinal vortices in the highly confined *** Fourier-transform decomposition of the Debye integral is employed to analyze the mechanism of the orbit-orbit *** is the first revelation of coupling between the longitudinal OAM and the transverse OAM,paving the way for potential applications in optical trapping,laser machining,nonlinear light-matter interactions,and more.

关键词： Spatiotemporal optical vortex Orbital angular momentum Momentum interaction Highly confined wavepacket Diffraction

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Event-Driven Attention Network:A Cross-Modal Framework for Efficient Image-Text Retrieval in Mass Gathering Events

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computers, Materials & Continua 2025年第5期83卷 3277-3301页

作者： Kamil Yasen Heyan Jin Sijie Yang Li Zhan Xuyang Zhang Ke Qin Ye Li School of Computer Science and Engineering University of Electronic Science and Technology of ChinaChengdu611731China School of Information and Software Engineering University of Electronic Science and Technology ofChinaChengdu611731China Kashi Institute of Electronics and Information Industry Kashi844508China

Research on mass gathering events is critical for ensuring public security and maintaining social ***,most of the existing works focus on crowd behavior analysis areas such as anomaly detection and crowd counting,and there is a relative lack of research on mass gathering *** believe real-time detection and monitoring of mass gathering behaviors are essential formigrating potential security risks and ***,it is imperative to develop a method capable of accurately identifying and localizing mass gatherings before disasters occur,enabling prompt and effective *** address this problem,we propose an innovative Event-Driven Attention Network(EDAN),which achieves image-text matching in the scenario of mass gathering events with good results for the first *** image-text retrieval methods based on global alignment are difficult to capture the local details within complex scenes,limiting retrieval *** local alignment-based methods aremore effective at extracting detailed features,they frequently process raw textual features directly,which often contain ambiguities and redundant information that can diminish retrieval efficiency and degrade model *** overcome these challenges,EDAN introduces an Event-Driven AttentionModule that adaptively focuses attention on image regions or textual words relevant to the event *** calculating the semantic distance between event labels and textual content,this module effectively significantly reduces computational complexity and enhances retrieval *** validate the effectiveness of EDAN,we construct a dedicated multimodal dataset tailored for the analysis of mass gathering events,providing a reliable foundation for subsequent *** conduct comparative experiments with other methods on our dataset,the experimental results demonstrate the effectiveness of *** the image-to-text retrieval task,EDAN achieved the best performance on the R@5 metric,w

关键词： Mass gathering events image-text retrieval attention mechanism

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Joint multiple resource allocation for offloading cost minimization in IRS-assisted MEC networks with NOMA

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Digital Communications and Networks 2023年第3期9卷 613-627页

作者： Guang Chen Yueyun Chen Zhiyuan Mai Conghui Hao Meijie Yang Shuangshuang Han Liping Du School of Computer and Communication Engineering University of Science and Technology BeijingBeijing100083China Shunde Innovition School of Unversity of Science and Technology Beijing

Effective resource allocation can exploit the advantage of intelligent reflective surface(IRS)assisted mobile edge computing(MEC)***,it is challenging to balance the limited energy of MTs and the strict delay requirement of their *** this paper,in order to tackle the challenge,we jointly optimize the offloading delay and energy consumption of mobile terminals(MTs)to realize the delay-energy tradeoff in an IRS-assisted MEC network,in which non-orthogonal multiple access(NOMA)and multiantenna are applied to improve spectral *** achieve the optimal delay-energy tradeoff,an offloading cost minimization model is proposed,in which the edge computing resource allocation,signal detecting vector,uplink transmission power,and IRS phase shift coefficient are needed to be jointly *** optimization of the model is a multi-level fractional problem in complex fields with some coupled high dimension *** solve the intractable problem,we decouple the original problem into a computing subproblem and a wireless transmission subproblem based on the uncoupled relationship between different variable *** computing subproblem is proved convex and the closed-form solution is obtained for the edge computing resource ***,the wireless transmission subproblem is solved iteratively through decoupling the residual *** each iteration,the closed-form solution of residual variables is obtained through different successive convex approximation(SCA)*** verify the proposed algorithm can converge to an optimum with polynomial *** results indicate the proposed method achieves average saved costs of 65.64%,11.24%,and 9.49%over three benchmark methods respectively.

关键词： Mobile edge computing Intelligent reflective surface Task offloading Multiple resource allocation Non-orthogonal multiple access

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Mitigation of Optical Multipath Interference Algorithms in IM-DD Transmission System

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China Communications 2024年第4期21卷 1-9页

作者： Huo Jiahao Zhu Jin Zhu Zuqing Zhang Xiaoying Liu Shaonan Tao Jianlong Wei Huangfu School of Computer and Communication Engineering University of Science and Technology BeijingBeijing 100083China School of Information Science and Technology University of Science and Technology of ChinaHefei 230026China

This paper aimed to propose two algorithms,DA-M and RF-M,of reducing the impact of multipath interference(MPI)on intensity modulation direct detection(IM-DD)systems,particularly for four-level pulse amplitude modulation(PAM4)***-M reduced the fluctuation by averaging the signal in blocks,RF-M estimated MPI by subtracting the decision value of the corresponding block from the mean value of a signal block,and then generated interference-reduced samples by subtracting the interference signal from the product of the corresponding MPI estimate and then weighting *** paper firstly proposed to separate the signal before decision-making into multiple blocks,which significantly reduced the complexity of DA-M and *** results showed that the MPI noise of 28 GBaud IMDD system under the linewidths of 1e5 Hz,1e6 Hz and 10e6 Hz can be effectively alleviated.

关键词： IM-DD multipath interference PAM4

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