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8th International Conference on Intelligent Computing and signal processing, ICSP 2023

作者： Hu, YongQi Cai, ZhongWang Nie, ZiJun Yu, ZiZheng Cao, Ying Yin, Zhijian Yang, Zhen Jiangxi Science and Technology Normal University School of Communications and Electronics Nanchang China Ministry of Education Key Laboratory of System Control and Information Processing Shanghai China

ISBN: (纸本)9798350302455

Given the requirements for robust target classification and accurate target state estimation in visual tracking, SiamFC++ proposes a set of practical guidelines for designing high-performance general-purpose trackers by considering the special nature of visual tracking problems. Inspired by dynamic modules, We propose an empirical method for integrating a dynamic module into the image input, which is concatenated with the template module after feature maps are extracted by the backbone network. Since the position and shape of the object can change significantly within a video sequence, the added dynamic module can better focus on the target region of the feature map to obtain better similarity maps. Extensive experiments and comparisons demonstrate that our simple and effective method achieves reliable results on the benchmarks of LaSOT, TrackingNet, and GOT-10K and provides a significant speed advantage in real-time. © 2023 IEEE.

关键词： Computer vision

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Joint Optimization of Privacy Protection and Resource Allocation for Vehicular Edge Networks

Joint Optimization of Privacy Protection and Resource Alloca...

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2023 IEEE/CIC International Conference on Communications in China, ICCC 2023

作者： Gao, Tianqi Tao, Hongfeng Ni, Yuanzhi Shi, Jun Jiang, Fengcheng Jiangnan University School of Internet of Things Engineering Wuxi214122 China Ministry of Education Key Laboratory of System Control and Information Processing Shanghai200240 China

ISBN: (纸本)9798350345384

In the last decade, the service of vehicular networks has benefited from the rapid development of advanced communication and computing technologies including edge computing. For vehicular network operators, it is valuable to study how to realize the accurate allocation of edge computing resource on the premise of protecting users' privacy. In this paper, we design a histogram publishing algorithm based on differential privacy. The algorithm first classifies tasks according to the characteristics of computing requests, then interferes categorized tasks and designs a shuffling algorithm based on Blum Blum Shub (BBS). Finally, the frequency histogram of computing resource is obtained by post-processing of the Expectation-Maximum (EM) algorithm. The simulation results verify the accuracy and superiority of the proposed histogram publishing algorithm by comparing it with the existing methods. © 2023 IEEE.

关键词： Edge computing

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Vehicle Platoon control Based on Information Exchanges in Internet of Vehicles 5th

Vehicle Platoon Control Based on Information Exchanges in ...

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5th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2021

作者： Gao, Tianqi Tian, Yuanxu Tao, Hongfeng Ni, Yuanzhi School of Internet of Things Engineering Jiangnan University Wuxi214122 China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China

ISBN: (纸本)9789811939976

Vehicle platooning is an emerging application in transportation system, boosting safe and efficient traffic environment. Based on the vehicular wireless communication technology, the driving states of the neighboring vehicles can be obtained for accurate vehicle control. In this work, the vehicle platoon system is modeled considering random characteristics of vehicular wireless communications. The consensus-based platoon control strategy and the autoregressive filtering algorithm are designed for efficient and effective control under topology of predecessor following (PF) and predecessor leading following (PLF), respectively. The platoon control model and algorithms are implemented by Simulink, where the results verify the effectiveness of the proposed solutions. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Time series analysis

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Semi-Supervised Learning for Low-Light Image Enhancement by Pseudo Low-Light Image 16

Semi-Supervised Learning for Low-Light Image Enhancement by ...

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16th International Congress on Image and signal processing, BioMedical Engineering and Informatics, CISP-BMEI 2023

作者： Xie, Shuo Ma, Yingjie Xu, Wei Qiu, Song Sun, Yifei East China Normal University School of Communication and Electronic Engineering China Ministry of Education Key Laboratory of System Control and Information Processing Shanghai200240 China

ISBN: (纸本)9798350330755

Building paired datasets in low-light enhancement entails significant cost and time, making such datasets precious commodities. Many researchers focus on how to enable models to learn more information from limited datasets. A prevalent strategy involves employing semi-supervised learning techniques to enhance model performance through additional unpaired images. However, one of the main challenges faced is the scarcity of a vast number of unpaired images from the same domain as the original low-light images. Consequently, we introduce a semi-supervised image enhancement method using pseudo-low-light images. Initially, we generate pseudo low-light images with less noise compared with the source domain image by the signal-to-Noise Ratio prior and diffusion models. We then employ the Mean-Teacher network and the feature constraints of the pseudo-low-light images to realize low-light image enhancement. Comprehensive experimental results validate the efficacy of our approach on real-world datasets. © 2023 IEEE.

关键词： Image enhancement

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Weed detection based on improved Yolov5 8

Weed detection based on improved Yolov5

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8th International Conference on Intelligent Computing and signal processing, ICSP 2023

作者： Yu, ZiZheng Nie, ZiJun Hu, Yong Qi Yan, HuangBin Lou, LiJun Yin, Zhijian Yang, Zhen Jiangxi Science and Technology Normal University School of Communications and Electronics Nanchang China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai China

ISBN: (纸本)9798350302455

The scale of grain production affects human life and development. With the continuous expansion of cultivated land, the reproductive ability of weeds to mutiply gradually increases, which affects the growth of crops. If weeds are not treated properly managed, they can also allow spread indiscriminately in the field and reduce crop yields. The growth ability of weeds is stronger than that of crops, and there are many types of weeds with a wide of species diversity. To solve the problem that the existing weed detection methods cannot detect and classify weeds accurately and quickly, a deep learning method based on improved Yolov5 was designed for weed detection. By replacing the 3 × 3 convolution with multi-head self-attention (MHSA) in the Yolov5's backbone, the accuracy of weed detection is improved. The experimental results show that the improved Yolov5 weed detection algorithm achieves 51.4% accuracy. Compared with the original Yolov5 model, the calculation amount is 3 points less than the original, and total time required is slightly shorter, which improves the accuracy of weed classification and positioning. © 2023 IEEE.

关键词： Crops

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Vertical Protection Level Optimization Method and Performance Analysis of ARAIM Based on PSA Algorithm 24

Vertical Protection Level Optimization Method and Performanc...

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4th Asia-Pacific Artificial Intelligence and Big Data Forum, AIBDF 2024

作者： Li, Mengjiao Han, Dan Tianjin Key Laboratory for Advanced Signal Processing Civil Aviation University of China Tianjin China Tianjin Air Traffic Control Sub-Branch North China Regional Air Traffic Management Bureau CAAC Tianjin China

ISBN: (纸本)9798400710865

Advanced Receiver Autonomous Integrity Monitoring (ARAIM) algorithm is one of the satellite navigation integrity enhancement technologies to assist civil aviation approach. The basic ARAIM algorithm distributes the integrity risk (IR) and continuity risk (CR) equally, leading to a conservative vertical protection level (VPL) and limiting the availability of ARAM. In this paper, a dynamic risk optimization allocation method PID-based search algorithm (PSA) is proposed. Using the minimum VPL as the optimization objective, iteratively search for the best risk allocation method assigned to each subset of faults while satisfying the constraints. And different optimization variables and objective functions are constructed to analyze the extent to which optimizing the allocation of both IR and CR risks versus optimizing the allocation of a single risk affects the level of protection. Experiments are conducted with static data from multi-GNSS experiment (MGEX) stations and vehicle-mounted dynamic data, and the experimental results show that under GPS and BDS dual-constellation observation, the ARAIM risk optimization allocation method based on the PSA algorithm can effectively reduce the VPL. The smallest VPL is obtained by optimizing the allocation of two risks at the same time, with an average optimization rate of up to 16.1%. And optimizing IR plays a more critical role in the overall protection level optimization, the magnitude of optimizing IR accounts for 68% of the complete optimization. © 2024 Copyright held by the owner/author(s).

关键词： Optimization algorithms

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Augmented Reality Enabled Telepresence Framework for Intuitive Robotic Teleoperation

Augmented Reality Enabled Telepresence Framework for Intuiti...

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2023 IEEE International Conference on Robotics and Biomimetics, ROBIO 2023

作者： Xu, Zheng Lin, Zecai Liu, Huanghua Ren, Qingsong Gao, Anzhu Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education Institute of Medical Robotics and Department of Automation Shanghai200240 China

ISBN: (纸本)9798350325706

In terms of telepresence for robotic teleoperation, the existing remote surgery provides the patient's side real-time videos to remote operators. Its effectiveness is limited due to the lack of depth information, occlusion, and restricted viewing angles. To address it, this paper develops a robotic telepresence framework integrating augmented reality (AR) and 3D reconstruction technology, providing a 3D virtual patient's side environment for remote operators. The real scene of the patient's side is reconstructed by a monocular camera with a manipulator before the operation, and the manipulator is teleoperated by the operator at the remote's side. The manipulator's pose is fused into the classic SVO+REMODE algorithm to improve the reconstructed accuracy. On the remote's side, an AR head-mounted display (HMD) is deployed to provide telepresence for operators under a similar environment, and the reconstructed scene of the patient's side is registered to the remote room, from which the operator can see the whole scene of the patient body and surrounding objects. An ArUco cube is used to evaluate the superimposed error between virtual and real displays, and the effectiveness is validated in an experimental platform for remote surgery. © 2023 IEEE.

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Smoke Detection In Complex Scenery using Improved YOLOV5 8

Smoke Detection In Complex Scenery using Improved YOLOV5

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8th International Conference on Intelligent Computing and signal processing, ICSP 2023

作者： Nie, ZiJun Hu, YongQi Yu, ZiZheng Li, RuJia Yin, ZhiJian Zhan, HuaLin Yang, Zhen Jiangxi Science and Technology Normal University School of Communications and Electronics Nanchang China Ministry of Education Key Laboratory of System Control and Information Processing Shanghai China

ISBN: (纸本)9798350302455

Considering smoke detection in a complex scene, high smoke object error rate and low detection efficiency, an improved YOLOV5 for smoke detection is proposed in this paper. To improve the effectiveness of smoke detection algorithm for smoke targets in complex scenes. First, a new lightweight convolution technique GSConv is introduced to replace the Conv layer in the neck layer for feature extraction, and the original C3 module is replaced by Cross Stage Partial Network (GSCSP) module VoVGSCSP. This improvement reduces the computation complexity of the algorithm while maintaining the detection accuracy. Second, CIoU is replaced by SIoU as the regression function of the prediction box to improve the prediction accuracy of the prediction box and reduce the rate of missed detection of the target. Finally, to improve the performance of the deep network, Dynamic ReLU is introduced as an activation function (dynamically adjusting the ReLU parameters depending on the input data). Experiments on the SM-dataset (smoke detection dataset) show that the improved model improves the accuracy and precision of target smoke detection compared to the YOLOV5 model. Its precision is increased by 1.8%, mAP@0.5 is increased by 1.0%, the complexity of the model is reduced by 23.8%. The improved algorithm proposed in this paper can effectively extract smoke features and more suitable for smoke detection tasks in complex scenes. © 2023 IEEE.

关键词： Smoke

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Research on Target Detection Based on Clustering and Hough Transform

Research on Target Detection Based on Clustering and Hough T...

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2022 International Conference on Statistics, Data Science, and Computational Intelligence, CSDSCI 2022

作者： Luo, Yanpeng Xiong, Jinyu Yang, Yuxiang Zhu, Mingjun Zhang, Tongxin Cheng, Haibing College of Information System Engineering PLA Strategic Support Force Information Engineering University Zhengzhou China National Key Laboratory of Science and Technology on Blind Signal Processing Chengdu China

ISBN: (纸本)9781510661325

Formation target track sorting is an important problem in multi-target track processing. Unlike the processing of periodic scans and point tracks of active radar, passive positioning data has the problems of irregular positioning period and difficulty in distinguishing multiple targets by target signal attributes. In this paper, we propose a track initiation algorithm for passive positioning system based on density clustering and Hough transform for the characteristics of passive positioning system. The algorithm first uses the density clustering algorithm to identify the cluster centers of targets with large measurement errors, and then uses the Hough transform method to initiate a track. © 2023 SPIE.

关键词： Hough transforms

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Semi-Autonomous Navigation Based on Local Semantic Map for Mobile Robot

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Journal of Shanghai Jiaotong university(Science) 2025年第1期30卷 27-33页

作者： ZHAO Yanfei XIAO Peng WANG Jingchuan GUO Rui Department of Automation Institute of Medical RoboticsShanghai Jiao Tong UniversityShanghai200240China State Key Laboratory of System Control and Information Processing Ministry of Education of ChinaShanghai200240China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240China State Grid Intelligence Technology Co. Ltd.Jinan250013China

Mobile robots represented by smart wheelchairs can assist elderly people with mobility *** paper proposes a multi-mode semi-autonomous navigation system based on a local semantic map for mobile robots,which can assist users to implement accurate navigation(e.g.,docking)in the environment without prior *** order to overcome the problem of repeated oscillations during the docking of traditional local path planning algorithms,this paper adopts a mode-switching method and uses feedback control to perform docking when approaching semantic *** last,comparative experiments were carried out in the real *** show that our method is superior in terms of safety,comfort and docking accuracy.

关键词： semi-autonomous navigation mobile robot semantic map voice interaction

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