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检索条件"机构=Measurement and Control Technology"

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DEEP CNN FUSING ATTENTION AND LGBM CLASSIFIER FOR HIGH-ACCURACY HAND GESTURE RECOGNITION 10

DEEP CNN FUSING ATTENTION AND LGBM CLASSIFIER FOR HIGH-ACCUR...

引用

10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： You, Zhicong Lu, Wangdong Zhu, Chunmei Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science & Technology University Beijing China

ISBN: (纸本)9781837242672

Gesture recognition has been widely used in automation and medical and smart-home. The adaptability and accuracy of traditional machine learning algorithms are limited by feature extraction and classifier selection, and the recognition accuracy is low as well as the robustness is poor. In our work, an improved CNN (Convolutional Neural Networks) combined with an LGBM (Lightweight Gradient Boosting Machine) hand gesture recognition method is proposed to improve the performance of hand gesture recognition. The method designs a 4-layer CNN structure and integrates a CBAM (Convolutional Block Attention Module) in the network to enhance the model's ability to learn and extract features. Furthermore, the extracted features are fed into an LGBM classifier for gesture classification, which improves the accuracy of gesture classification and reduces the risk of model overfitting. The accuracy of the 16 types of static gesture recognition reaches 97.89% in our dataset. An improvement of more than 10% is obtained in comparison with traditional machine learning classification algorithms. It demonstrates promising prospects for gesture recognition. © The Institution of Engineering & technology 2024.

关键词： Convolutional neural networks

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RESEARCH ON THREE-DIMENSIONAL FUSION METHOD OF SURVEILLANCE VIDEO IN SMART PARK 10

RESEARCH ON THREE-DIMENSIONAL FUSION METHOD OF SURVEILLANCE ...

引用

10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： Li, Haowei Zuo, Yunbo Hu, Huan Chen, Sai Zheng, Yifan Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing China

ISBN: (纸本)9781837242672

The three-dimensional video fusion technology is increasingly becoming an important part of smart parks. In previous security work, surveillance videos are typically displayed in a multi-screen layout, making it difficult to directly analyze the spatial positions of scenes and objects in the monitoring footage. Based on this, a real-time fusion rendering method for RTSP video streams and three-dimensional park models is proposed, which uses texture projection to integrate real videos into virtual three-dimensional models, achieving the fusion of multiple video sources. For scenarios with multiple videos at the same location, a viewpoint-based weighted method is adopted to achieve texture overlay rendering. Finally, a smart park surveillance video fusion platform is built based on the *** framework, supporting real-time rendering on the web. The system also provides various interaction methods, including roaming and viewpoint switching, making it convenient for personnel to monitor key areas. Simultaneously, it achieves the effect of roaming in virtual three-dimensional scenes, enhancing the stereoscopic presentation of real scenes in surveillance videos. The system demonstration proves that effectively combining real-time surveillance videos with three-dimensional models results in better spatial presentation of videos and enhances the ability to discern the actual positions of scenes within the smart park. © The Institution of Engineering & technology 2024.

关键词： Rendering (computer graphics)

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SMOKING BEHAVIOR DETECTION BASED ON IMPROVED YOLOV7 OBJECT ASSOCIATION 10

SMOKING BEHAVIOR DETECTION BASED ON IMPROVED YOLOV7 OBJECT A...

引用

10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： Chen, Sai Zuo, Yunbo Hu, Huan Zheng, Yifan Li, Haowei Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing China

ISBN: (纸本)9781837242672

To address the security risks caused by unauthorized individuals smoking in public places, a method for detecting smoking behavior based on an improved YOLOv7 target association is proposed. First, the improved YOLOv7 algorithm is used to detect the people and cigarette targets in the image, and then the distance relationship between the center coordinates of the cigarette target detection frame and the person target detection box is calculated, and the correlation between the two is located to determine whether there is smoking behavior. The improved YOLOv7 algorithm introduces the CBAM attention module to prioritize key areas and diminish background interference. Simultaneously, the SIOU loss function is employed to bolster the precision of the regression outcomes. Experiments conducted on the test dataset reveal that the proposed approach achieves an accuracy of 91.35% and a detection speed of 78 FPS, achieving real-time accurate detection effects. © The Institution of Engineering & technology 2024.

关键词： IMPROVED YOLOV7 OBJECT ASSOCIATION SMOKING BEHAVIOR DETECTION

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HAND-TO-EYE CALIBRATION OF A ROBOTIC ARM USING POINT CLOUD REGISTRATION METHOD 10

HAND-TO-EYE CALIBRATION OF A ROBOTIC ARM USING POINT CLOUD R...

引用

10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： Miao, Zhuoran Zuo, Yunbo Hu, Huan Ge, Xiaoliang Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing China

ISBN: (纸本)9781837242672

The objective of this paper is to investigate a hand-eye calibration approach employing an eye-to-hand configuration, focusing on point cloud registration. In the initial segments of the paper, the paper delineate the core principles that underpin hand-eye calibration, as well as the various techniques that are predominantly utilized in this field. Furthermore, the article meticulously analyzes the limitations of the traditional methods and identifies potential areas where improvements can be made. Subsequently, it delves into the hand-eye calibration methodology grounded in 3D point cloud registration. This exploration includes an in-depth analysis of an enhanced version of the Super 4PCS Algorithm-based point cloud registration algorithm, which is a novel and effective method for point cloud registration. Additionally, the article discusses the intricacies of coordinate system transformation and provides a comprehensive explanation of how to solve the hand-eye calibration equation AX=XB using the navy method. Furthermore, the paper empirically validates the efficacy and precision of this method. This validation process involves a comparative analysis with other existing approaches. Lastly, it summarizes the research findings and discusses the strengths and limitations of the proposed method. © The Institution of Engineering & technology 2024.

关键词： Robotic arms

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A high performance stacked band-pass filter with frequency doubling suppression

A high performance stacked band-pass filter with frequency d...

引用

2024 International Applied Computational Electromagnetics Society Symposium, ACES-China 2024

作者： Wu, Wenhan Xu, Ruofeng Wang, Jun Zhao, Lei Hu, Yunze Pan, Guoqing China University of Mining and Technology School of Information and Control Engineering Xuzhou China Beijing Aerospace Measurement and Control Technology Co. Ltd Beijing China

ISBN: (纸本)9798350355581

In this paper, a high performance stacked bandpass filter based on frequency doubling suppression is proposed. The proposed filter consists of an interdigital structure and a stepped impedance resonator (SIR). The two structures are combined in a laminated manner and connected by vertical metal vias. The filter has compact size, excellent passband performance and wide stopband. The proposed miniaturized bandpass filter is expected to be applied in modern communication systems. © 2024 IEEE.

关键词： Bandpass filters

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Feature Mining Method Based on Deep Learning for Underwater Electric Field Prediction in Marine Environment

Feature Mining Method Based on Deep Learning for Underwater ...

引用

2023 European Conference on Communication Systems, ECCS 2023

作者： Cui, Pei Jiang, Kaina Yue, Jin Wu, Yuanzhe Fu, Yibo Science and Technology on Underwater Test and Control Laboratory Dalian China Dalian Institute of Measurement and Control Technology Dalian China

ISBN: (纸本)9798350323344

The low-frequency electric field generated by various electromagnetic effects in the ocean overwrites the useful signal in amplitude and frequency, as a background distraction field for electric field detection. Effective electric field characteristic analysis and prediction methods are helpful to improve the environmental adaptability of the equipment and the ability of target detection. The deep learning method is used to mine the characteristics of underwater electric field in the marine environment to improve the prediction accuracy. In order to explore the relationship between seawater environmental parameters and electric field characteristics, parameters including measure time, seawater conductivity, water depth and wave height are used as independent variables, and the amplitude of the underwater electric field in the marine environment is used as the dependent variable. The relationship model between independent variables and dependent variables are established by deep neural network training to realize the prediction of underwater electric field characteristics in the marine environment. The results of 103 training samples and 2 test samples show that the method can effectively identify the test samples, and can be used for the mining and prediction of underwater electric field characteristics, as well as the detection and identification of weak electric field signals submerged in the marine environment. © 2023 IEEE.

关键词： Forecasting

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DENSE POINT CLOUD MAP CONSTRUCTION BASED ON ORB-SLAM2 AND CROSS-ATTENTION NETWORK 10

DENSE POINT CLOUD MAP CONSTRUCTION BASED ON ORB-SLAM2 AND CR...

引用

10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： Liu, Yizheng Su, Qinghua Song, Yue Zhang, Pengbo Xie, Zhihao Wang, Liyong Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science & Technology University Beijing China

ISBN: (纸本)9781837242672

In the field of 3D vision technology, binocular vision technology, as a representative of low-cost and high-efficiency methods, has gained widespread attention and holds superior application prospects in the industrial sector. The current state-of-the-art binocular sparse visual SLAM systems can accurately and reliably estimate camera trajectories and landmark positions. However, these sparse maps are solely used for localization and cannot be employed for other tasks such as obstacle avoidance or scene understanding. To address this, this paper proposes a framework for constructing dense point cloud maps in binocular sparse visual SLAM systems. This framework enhances the traditional ORB-SLAM2 algorithm by incorporating depth estimation using a cross-attention network to complete depth information and build dense point cloud maps based on its localization capabilities. For the first-frame image, the proportion of incorrectly predicted pixels in the KITTI dataset is only 1.77%. The proposed method is effective and robust on common datasets, suitable for constructing dense point cloud maps in outdoor large-scale scenes. The output model is overall comprehensive and detailed, holding significant practical value in various outdoor scenarios. © The Institution of Engineering & technology 2024.

关键词： Binoculars

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FAULT DIAGNOSIS METHOD BASED ON THE TIMESNET MODEL UNDER VARIABLE SPEED AND STRONG NOISE 10

FAULT DIAGNOSIS METHOD BASED ON THE TIMESNET MODEL UNDER VAR...

引用

10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： Qiao, Wan Liu, Xiuli Huang, Jinpeng Wu, Guoxin Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing China

ISBN: (纸本)9781837242672

Aiming at the fault diagnosis of rotating machinery in industrial production, which faces the problems of signal noise, variable speed and other interferences that lead to inconspicuous fault features, and the traditional methods rely on manual experience for feature extraction and lack of robustness, the present study introduces a novel fault diagnosis approach utilizing the TimesNet model. This method takes the temporal multi-periodicity as the starting point, and the one-dimensional original signal is divided into multiple two-dimensional signals by different sizes of the period respectively. Subsequently, Inception-Attention modeling is applied to extract intricate time and space information. The experiments use the planetary gearbox dataset to verify the influence of different parameters and structures of TimesNet on the diagnostic effect, and carry out comparative tests with five time-series classification models, which provide some reference value for the application of TimesNet in fault diagnosis. © The Institution of Engineering & technology 2024.

关键词： Epicyclic gears

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REVIEW OF RESEARCH ON OCCLUSION ISSUES IN RGB-D DYNAMIC SCENE 3D RECONSTRUCTION 10

REVIEW OF RESEARCH ON OCCLUSION ISSUES IN RGB-D DYNAMIC SCEN...

引用

10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： Dong, Yuanqiu Wu, Guoxin Zhang, Guolong Zhou, Linglong Qi, Yinyan The Ministry of Education Key Laboratory of Modern Measurement and Control Technology Beijing Information Science & Technology University Beijing China

ISBN: (纸本)9781837242672

As innovation proceeds to advance,3D recreation innovation has ended up a critical portion of the field of computer vision. Among these, 3D reproduction innovation based on RGB-D information sources has ended up a well known approach in later a long time. Right now, the more develop inactive 3D recreation calculations have ended up progressively successful for reproducing stationary objects. Be that as it may, their adequacy lessens when parts of the scene are blocked. This paper briefly presents particular approaches to address impediment issues and the fundamental concepts of energetic 3D remaking innovation based on RGB-D information sources. The points of interest and current investigate status of energetic 3D reproduction focusing on impediment issues utilizing RGB-D information sources are examined. Moreover, the most recent progressions in 3D remaking of energetic scenes are summarized, and proposed future investigate bearings. © The Institution of Engineering & technology 2024.

关键词： 3D reconstruction

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REARCH ON DOUBLE CUBIC INTERPOLATION COMBINED WITH GAUSSIAN FITTING SUB-PIXEL EDGE DETECTION METHOD 10

REARCH ON DOUBLE CUBIC INTERPOLATION COMBINED WITH GAUSSIAN ...

引用

10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： Qi, Yinyan Wu, Guoxin Li, Yao Dong, Yuanqiu The Ministry of Education Key Laboratory of Modern Measurement and Control Technology Beijing Information Science & Technology University Beijing China

ISBN: (纸本)9781837242672

With the rapid advancements in intelligent manufacturing technology, the realization of fast and accurate measurements in aerospace, instrumentation, machinery and equipment, automotive electronics, and other sectors has become a research hotspot. Image positioning technology and edge detection methods, with their advantages of being fast, non-contact, and precise, have been widely employed. How to improve the accuracy of image measurement lies in solving the problem of accurate positioning of image edge detection, based on the problem of inaccurate extraction of directional information and large error in contour size of image edge detection technology proposes an improved sub-pixel edge detection algorithm with Gaussian fitting by double cubic interpolation. Based on preprocessing for pixel-level edge feature extraction, pixel-level edge points are acquired utilizing the least squares fitting algorithm. The normal section is determined by computing the normal intercept line, while the normal isometric line is identified through the Gaussian integration method. Sub-pixel fitting points are obtained via boundary fitting, and the final grey value is derived using an edge detection algorithm that combines double cubic interpolation and Gaussian fitting on the fitted points. The experimental results demonstrate that, through comparative testing of this method, it has been verified that it exhibits the highest image quality and is superior to most current algorithms. An improvement in the algorithm by 0.021%, 0.025%, and 0.031% in edge localization accuracy compared to the Zernike moment algorithm, Gaussian fitting algorithm, and bicubic interpolation algorithm has been achieved, effectively verifying that the image quality detected by this method is relatively high. In comparison with the point cloud method regarding fitting error, it was observed that the error index increased by 0.025% under strong burst light conditions, 0.026% under normal burst light conditions, an

关键词： Interpolation

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