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  • Open Access

    ARTICLE

    Learning Dual-Domain Calibration and Distance-Driven Correlation Filter: A Probabilistic Perspective for UAV Tracking

    Taiyu Yan1, Yuxin Cao1, Guoxia Xu1, Xiaoran Zhao2, Hu Zhu1, Lizhen Deng3,*

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3741-3764, 2023, DOI:10.32604/cmc.2023.039828

    Abstract Unmanned Aerial Vehicle (UAV) tracking has been possible because of the growth of intelligent information technology in smart cities, making it simple to gather data at any time by dynamically monitoring events, people, the environment, and other aspects in the city. The traditional filter creates a model to address the boundary effect and time filter degradation issues in UAV tracking operations. But these methods ignore the loss of data integrity terms since they are overly dependent on numerous explicit previous regularization terms. In light of the aforementioned issues, this work suggests a dual-domain Jensen-Shannon divergence correlation filter (DJSCF) model address… More >

  • Open Access

    ARTICLE

    An Improved Calibration Method of Grating Projection Measurement System

    Qiucheng Sun*, Weiyu Dai, Mingyu Sun, Zeming Ren, Mingze Wang

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3957-3970, 2023, DOI:10.32604/cmc.2023.037254

    Abstract In the traditional fringe projection profilometry system, the projector and the camera light center are both spatially virtual points. The spatial position relationships specified in the model are not easy to obtain, leading to inaccurate system parameters and affecting measurement accuracy. This paper proposes a method for solving the system parameters of the fringe projection profilometry system, and the spatial position of the camera and projector can be adjusted in accordance with the obtained calibration parameters. The steps are as follows: First, in accordance with the conversion relationship of the coordinate system in the calibration process, the calculation formula of… More >

  • Open Access

    ARTICLE

    Prediction of Uncertainty Estimation and Confidence Calibration Using Fully Convolutional Neural Network

    Karim Gasmi1,*, Lassaad Ben Ammar2,, Hmoud Elshammari4, Fadwa Yahya2

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2557-2573, 2023, DOI:10.32604/cmc.2023.033270

    Abstract Convolution neural networks (CNNs) have proven to be effective clinical imaging methods. This study highlighted some of the key issues within these systems. It is difficult to train these systems in a limited clinical image databases, and many publications present strategies including such learning algorithm. Furthermore, these patterns are known for making a highly reliable prognosis. In addition, normalization of volume and losses of dice have been used effectively to accelerate and stabilize the training. Furthermore, these systems are improperly regulated, resulting in more confident ratings for correct and incorrect classification, which are inaccurate and difficult to understand. This study… More >

  • Open Access

    ARTICLE

    Easy to Calibrate: Marker-Less Calibration of Multiview Azure Kinect

    Sunyoung Bu1, Suwon Lee2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 3083-3096, 2023, DOI:10.32604/cmes.2023.024460

    Abstract Reconstructing a three-dimensional (3D) environment is an indispensable technique to make augmented reality and augmented virtuality feasible. A Kinect device is an efficient tool for reconstructing 3D environments, and using multiple Kinect devices enables the enhancement of reconstruction density and expansion of virtual spaces. To employ multiple devices simultaneously, Kinect devices need to be calibrated with respect to each other. There are several schemes available that calibrate 3D images generated from multiple Kinect devices, including the marker detection method. In this study, we introduce a markerless calibration technique for Azure Kinect devices that avoids the drawbacks of marker detection, which… More > Graphic Abstract

    Easy to Calibrate: Marker-Less Calibration of Multiview Azure Kinect

  • Open Access

    ARTICLE

    ER-Net: Efficient Recalibration Network for Multi-View Multi-Person 3D Pose Estimation

    Mi Zhou1, Rui Liu1,*, Pengfei Yi1, Dongsheng Zhou1,2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 2093-2109, 2023, DOI:10.32604/cmes.2023.024189

    Abstract Multi-view multi-person 3D human pose estimation is a hot topic in the field of human pose estimation due to its wide range of application scenarios. With the introduction of end-to-end direct regression methods, the field has entered a new stage of development. However, the regression results of joints that are more heavily influenced by external factors are not accurate enough even for the optimal method. In this paper, we propose an effective feature recalibration module based on the channel attention mechanism and a relative optimal calibration strategy, which is applied to the multi-view multi-person 3D human pose estimation task to… More > Graphic Abstract

    ER-Net: Efficient Recalibration Network for Multi-View Multi-Person 3D Pose Estimation

  • Open Access

    ARTICLE

    Traceability Technology of DC Electric Energy Metering for On-Site Inspection of Chargers

    Hua Li1,*, Dezhi Xiong2,3, Zhi Wang2,3

    Energy Engineering, Vol.120, No.3, pp. 715-727, 2023, DOI:10.32604/ee.2022.022990

    Abstract The on-site inspection of high-power DC chargers results in new DC high-current measurement and DC energy traceability system requirements. This paper studies the traceability technology of electric energy value for automotive high-power DC chargers, including: (1) the traceability method of the built-in DC energy meter and shunt of the charger; (2) precision DC high current and small precision DC voltage output and measurement technology. This paper designs a 0.1 mA~600 A DC high current measurement system and proposes a 0.005 level DC power measurement traceability system. The uncertainty evaluation experiment of the DC power measurement calibration system and the high-power… More >

  • Open Access

    ARTICLE

    Design of Ka-Band Phased Array Antenna with Calibration Function

    Xiao Liu1,2, Xingyao Zeng1,*, Chengxiang Hao1, Haibo Zhang1, Zhongjun Yu1,2, Ting Lv3, Meng Li4, Zhen Zhang5

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6251-6261, 2023, DOI:10.32604/cmc.2023.027114

    Abstract In this paper, we have proposed a novel structure of Ka-band based phased array antenna with calibration function. In the design of Ka-band antenna, the active phased array system is adopted and the antenna would work in the dual polarization separation mode. We have given out the schematic diagram for the proposed Ka-band antenna, where the Ka-band antenna is in the form of waveguide slot array antenna, with 96 units in azimuth and 1 unit in distance. Each group of units is driven by a single-channel Transmitter/Receiver (T/R) component, and the whole array contains 192 T/R components in total. The… More >

  • Open Access

    ARTICLE

    Research on Rainfall Estimation Based on Improved Kalman Filter Algorithm

    Wen Zhang1,2, Wei Fang1,3,*, Xuelei Jia1,2, Victor S. Sheng4

    Journal of Quantum Computing, Vol.4, No.1, pp. 23-37, 2022, DOI:10.32604/jqc.2022.026975

    Abstract In order to solve the rainfall estimation error caused by various noise factors such as clutter, super refraction, and raindrops during the detection process of Doppler weather radar. This paper proposes to improve the rainfall estimation model of radar combined with rain gauge which calibrated by common Kalman filter. After data preprocessing, the radar data should be classified according to the precipitation intensity. And then, they are respectively substituted into the improved filter for calibration. The state noise variance and the measurement noise variance can be adaptively calculated and updated according to the input observation data during this process. Then… More >

  • Open Access

    ARTICLE

    Friction Coefficient Calibration of Sunflower Seeds for Discrete Element Modeling Simulation

    Shuai Wang, Zhihong Yu*, Wenjie Zhang, Dongxu Zhao, Aorigele

    Phyton-International Journal of Experimental Botany, Vol.91, No.11, pp. 2559-2582, 2022, DOI:10.32604/phyton.2022.021354

    Abstract

    Sunflower (Helianthus annuus L.) is one of the four major oil crops in the world and has high economic value. However, the lack of discrete element method (DEM) models and parameters for sunflower seeds hinders the application of DEM for computer simulation in the key working processes of sunflower seed sowing and harvesting. The present study was conducted on two varieties of sunflower, and the DEM model of sunflower seeds was established by using 3D scanning technology based on the distribution of triaxial dimensions and volumes of the geometric model of sunflower seeds. Similarly, the physical characteristics parameters of sunflower… More >

  • Open Access

    ARTICLE

    Resource Based Automatic Calibration System (RBACS) Using Kubernetes Framework

    Tahir Alyas1, Nadia Tabassum2, Muhammad Waseem Iqbal3,*, Abdullah S. Alshahrani4, Ahmed Alghamdi5, Syed Khuram Shahzad6

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 1165-1179, 2023, DOI:10.32604/iasc.2023.028815

    Abstract Kubernetes, a container orchestrator for cloud-deployed applications, allows the application provider to scale automatically to match the fluctuating intensity of processing demand. Container cluster technology is used to encapsulate, isolate, and deploy applications, addressing the issue of low system reliability due to interlocking failures. Cloud-based platforms usually entail users define application resource supplies for eco container virtualization. There is a constant problem of over-service in data centers for cloud service providers. Higher operating costs and incompetent resource utilization can occur in a waste of resources. Kubernetes revolutionized the orchestration of the container in the cloud-native age. It can adaptively manage… More >

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