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Optimization Algorithm of RGB-D SLAM Visual Odometry based on Triangulation

International Journal of Performability engineering 2020年第3期16卷 438-445页

作者： Dong, Jingwei Jiang, Yiming Han, Zhiyu School of Measure Control Technology and Communication Engineering Harbin University of Science and Technology Harbin150080 China

In this paper, an improved RGB-D SLAM scheme is proposed to solve the problems of great tracking error, long time-consuming in front-end, and high pressure of algorithm in back-end. The realization scheme is mainly aimed at improving the visual odometry. First, the ORB extraction algorithm is used to extract the feature points of the current frame and calculate the descriptors. Then, the current frame is matched with the local map by descriptors, and the matched feature points are added to the local map. Finally, the camera pose is calculated by the PnP algorithm. In order to ensure the tracking accuracy, a triangulation algorithm is proposed to optimize the depth value of map points in the local map. A series of fr1 datasets in the tum database are tested. The experimental results show that the real-time performance is guaranteed, and the RMSE (root mean square error) in the tracking process is reduced by 9% on average. Moreover, the image indexes of the point cloud image generated in the tracking process are also significantly improved. © 2020 Totem Publisher, Inc. All rights reserved.

关键词： Triangulation

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A new method for realizing LOG filter in image edge detection

A new method for realizing LOG filter in image edge detectio...

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6th International Forum on Strategic technology, IFOST 2011

作者： Xu, Jingbo Liu, Bo Lin, Haijun Li, Jianxin College of Measure-control Technology and Communication Engineering Harbin University of Science and Technology Harbin 150080 China Higher Educational Key Laboratory for Measuring and Control Technology Instrumentations of Heilongjiang Province Harbin 150080 China

ISBN: (纸本)9781457703966

LOG filter for image edge detection consists of Gaussian filter and Laplace operator. Based on the central limit theorem and the separating characteristic of two dimensional Gaussian filter, Gaussian approximation filter is constructed. The digital filtering algorithm for Gaussian approximation filter is concluded through the bilinear transformation method and zero phase shift filtering technology. The algorithm combined with the Laplace operator has been successfully applied in the implementation of LOG filtering for edge detection. Applying Gaussian approximation filter in LOG filtering is helpful for multi-scale LOG filtering because only one parameter in the algorithm needs to be changed. This method is more convenient than the template method in which the coefficients of the whole mask of LOG filter with different scale need to be refreshed. This is a new implementation for LOG filter. © 2011 IEEE.

关键词： Laplace transforms

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Incremental Learning of Radio Modulation Classification Based on Sample Recall

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China communications 2023年第7期20卷 258-272页

作者： Yan Zhao Shichuan Chen Tao Chen Weiguo Shen Shilian Zheng Zhijin Zhao Xiaoniu Yang School of Communication Engineering Hangzhou Dianzi UniversityHangzhou 310018China Science and Technology on Communication Information Security Control Laboratory Jiaxing 314033China Institute of Cyberspace Security Zhejiang University of TechnologyHangzhou 310023China

Radio modulation classification has always been an important technology in the field of *** difficulty of incremental learning in radio modulation classification is that learning new tasks will lead to catastrophic forgetting of old *** this paper,we propose a sample memory and recall framework for incremental learning of radio modulation *** data with different signal-to-noise ratios,we use a partial memory strategy by selecting appropriate samples for *** compare the performance of our proposed method with three baselines through a large number of simulation *** show that our method achieves far higher classification accuracy than finetuning method and feature extraction ***,it performs closely to joint training method which uses all old data in terms of classification accuracy which validates the effectiveness of our method against catastrophic forgetting.

关键词： radio modulation classification incremen-tal learning deep learning convolutional neural net-work.

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Lighting control with Myo armband based on customized classifier

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The Journal of China Universities of Posts and Telecommunications 2022年第4期29卷 106-116页

作者： Jiang Yujian Yang Xue Zhang Junming Song Yang Key Laboratory of Acoustic Visual Technology and Intelligent Control System Communication University of ChinaBeijing 100024China Beijing Key Laboratory of Modern Entertainment Technology Communication University of ChinaBeijing 100024China School of Information and Communication Engineering Communication University of ChinaBeijing 100024China

This paper focuses on gesture recognition and interactive lighting *** collection of gesture data adopts the Myo armband to obtain surface electromyography(sEMG).Considering that many factors affect sEMG,a customized classifier based on user calibration data is used for gesture *** this paper,machine learning classifiers k-nearest neighbor(KNN),support vector machines(SVM),and naive Bayesian(NB)classifier,which can be used in small sample sets,are selected to classify four gesture *** performance of the three classifiers under different training parameters,different input features,including root mean square(RMS),mean absolute value(MAV),waveform length(WL),slope sign change(SSC)number,zero crossing(ZC)number,and variance(VAR)are tested,and different input channels are also *** results show that:The NB classifier,which assumes that the prior probability of features is polynomial distribution,has the best performance,reaching more than 95%***,an interactive stage lighting control system based on Myo armband gesture recognition is implemented.

关键词： Myo armband gesture recognition surface electromyography customized classifier lighting control

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Failure Mode Analysis and Infrared Image Recognition of Crystalline Silicon PV Module 5

Failure Mode Analysis and Infrared Image Recognition of Crys...

引用

5th International Conference on Video, Signal and Image Processing, VSIP 2023

作者： Li, Ziyi Wang, Lijie Sun, Jianbo Lu, Xinyu Zhu, Xianwen School Of Measurement And Control Technology And Communication Engineering Harbin University Of Science And Technology China

ISBN: (纸本)9798400709272

In this paper, the fault analysis of crystalline silicon photovoltaic modules is studied. The Failure Mode and Effect Analysis (FMEA) and Fault Tree Analysis (FTA) methods are used to analyze the failure mode and its causes. Based on the results of fault analysis, the infrared image analysis and recognition methods are studied for the two fault modes of infrared hot spot and component shedding of Photovoltaic(PV) modules. The YOLOv5s image recognition method based on clustering improvement and feature enhancement is discussed. The experimental results show that the YOLOv5s image recognition algorithm with clustering improvement and feature enhancement improves the training effect of the model by using the EIOU loss function to adaptively adjust the confidence loss balance coefficient, and the detection speed (Frame Per Second, FPS) can reach 42.37 FPS;by adding InRe feature enhancement modules before each detection layer, the extraction ability of target features is improved. The mean Average Precision (mAP) of hot spot and component shedding are 94.85 % and 90.67 %, respectively, which can fully meet the needs of UAV automatic inspection. © 2023 ACM.

关键词： Silicon

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Approximation implementation approach for Gaussian filtering in roundness measurement

Approximation implementation approach for Gaussian filtering...

引用

6th International Forum on Strategic technology, IFOST 2011

ISBN: (纸本)9781457703966

Gaussian filter acts as the filter for roundness signal processing and a new implementation approach for Gaussian filter is presented. Based on the theory of B-spline function, the variational principle with the tension condition and the convolution characteristic of Gaussian filter with small scale, the approximation filter of Gaussian filter is concluded, which has the amplitude characteristic deviation from Gaussian filter less than 1% and the zero-phase-shift characteristic. The algorithm for the approximation filter consists of the zero-phase-shift filtering and the weighing filtering which loop two times. The algorithm is both simply in its structure and high in its filtering efficiency. The method of cycle continuation solves the edge effects of digital filtering based on the periodicity of the roundness measurement signal. The approximation filter is also efficient and accurate for the implementation of Gaussian filter in the application of roundness measurement. © 2011 IEEE.

关键词： Interpolation

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Impact Damage Identification of Aluminum Alloy Reinforced Plate Based on GWO-ELM Algorithm

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Structural Durability & Health Monitoring 2023年第6期17卷 485-500页

作者： Wei Li Benjian Zou Yuxiang Luo Ning Yang Faye Zhang Mingshun Jiang Lei Jia School of Control Science and Engineering Shandong UniversityJinan250061China Communication Technology Division Shandong Institute of Space Electronic TechnologyYantai264000China

As a critical structure of aerospace equipment,aluminum alloy stiffened plate will influence the stability of spacecraft in orbit and the normal operation of the *** this study,a GWO-ELM algorithm-based impact damage identification method is proposed for aluminum alloy stiffened panels to monitor and evaluate the damage condition of such stiffened panels of ***,together with numerical simulation,the experimental simulation to obtain the damage acoustic emission signals of aluminum alloy reinforced panels is performed,to establish the damage ***,the amplitude-frequency characteristics of impact damage signals are extracted and put into an extreme learning machine(ELM)model to identify the impact location and damage degree,and the Gray Wolf Optimization(GWO)algorithm is employed to update the weight parameters of the ***,experiments are conducted on the irregular aluminum alloy stiffened plate with the size of 2200 mm×500 mm×10 mm,the identification accuracy of impact position and damage degree is 98.90% and 99.55% in 68 test areas,*** experiments with ELM and backpropagation neural networks(BPNN)demonstrate that the impact damage identification of aluminum alloy stiffened plate based on GWO-ELM algorithm can serve as an effective way to monitor spacecraft structural damage.

关键词： GWO-ELM aluminum alloy stiffened plate damage identification amplitude-frequency characteristic

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Cognitive radio adaptation for power consumption minimization using biogeography-based optimization

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Chinese Physics B 2016年第12期25卷 499-506页

作者：齐佩汉郑仕链杨小牛赵知劲 School of Telecommunications Engineering Xidian University Xi'an 710071 China Science and Technology on Communication Information Security Control Laboratory Jiaxing 314033 China School of Telecommunications Hangzhou Dianzi University Hangzhou 310018 China

Adaptation is one of the key capabilities of cognitive radio, which focuses on how to adjust the radio parameters to optimize the system performance based on the knowledge of the radio environment and its capability and characteristics. In this paper, we consider the cognitive radio adaptation problem for power consumption minimization. The problem is formulated as a constrained power consumption minimization problem, and the biogeography-based optimization （BBO） is introduced to solve this optimization problem. A novel habitat suitability index （HSI） evaluation mechanism is proposed, in which both the power consumption minimization objective and the quality of services （QoS） constraints are taken into account. The results show that under different QoS requirement settings corresponding to different types of services, the algorithm can minimize power consumption while still maintaining the QoS requirements. Comparison with particle swarm optimization （PSO） and cat swarm optimization （CSO） reveals that BBO works better, especially at the early stage of the search, which means that the BBO is a better choice for real-time applications.

关键词： cognitive radio power consumption adaptation optimization

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An analysis method for correlation between catenary irregularities and pantograph-catenary contact force

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Journal of Central South University 2014年第8期21卷 3353-3360页

作者：秦勇张媛程晓卿贾利民邢宗义 State Key Laboratory of Rail Traffic Control and Safety (Beijing Jiaotong University) School of Mechanical Engineering Beijing Institute of Graphic Communication School of Automation Nanjing University of Science and Technology

Pantograph-catenary contact force provides the main basis for evaluation of current quality collection; however,the pantograph-catenary contact force is largely affected by the catenary *** analyze the correlated relationship between catenary irregularities and pantograph-catenary contact force,a method based on nonlinear auto-regressive with exogenous input(NARX) neural networks was ***,to collect the test data of catenary irregularities and contact force,the pantograph/catenary dynamics model was established and dynamic simulation was conducted using MATLAB/***,catenary irregularities were used as the input to NARX neural network and the contact force was determined as output of the NARX neural network,in which the neural network was trained by an improved training mechanism based on the regularization *** simulation results show that the testing error and correlation coefficient are 0.1100 and 0.8029,respectively,and the prediction accuracy is *** the comparisons with other algorithms indicate the validity and superiority of the proposed approach.

关键词： catenary irregularities pantograph-catenary contact force NARX neural networks correlation analysis

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Research on emotional space for movie and TV drama videos

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The Journal of China Universities of Posts and Telecommunications 2022年第5期29卷 73-82页

作者： Li Yujie Zhang Jingjing Jiang Wei Wang Chunxiao Key Laboratory of Acoustic Visual Technology and Intelligent Control System Communication University of ChinaBeijing 100024China Beijing Key Laboratory of Modern Entertainment Technology Communication University of ChinaBeijing 100024China School of Information and Communication Engineering Communication University of ChinaBeijing 100024China School of Computer and Cyber Sciences Communication University of ChinaBeijing 100024China

Emotional space refers to a multi-dimensional emotional model that describes a group of subjective feelings or emotions. Since the existing discrete emotional space is mainly aimed at human’s primary emotions, it cannot describe the complex emotions evoked when watching movies. In order to solve this problem, an emotional fusion space for videos was constructed by selecting movies and TV dramas with rich emotional semantics as the research objects. Firstly, emotional words based on movie and TV drama videos are acquired and analyzed by using subjective evaluation and semantic analysis methods. Then, the emotional word vectors obtained from the above analysis are fused, reduced dimension by t-distributed stochastic neighbor embedding(t-SNE) algorithm, and clustered by bisecting K-means clustering algorithm to get a discrete emotional space for movie and TV drama videos. This emotional fusion space can obtain different categories by changing the value of the emotion classification number without re-labeling and calculation.

关键词： emotional space movie and TV drama videos subjective evaluation words semantic analysis fusion space

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