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  • Open Access

    ARTICLE

    Target Detection on Water Surfaces Using Fusion of Camera and LiDAR Based Information

    Yongguo Li, Yuanrong Wang, Jia Xie*, Caiyin Xu, Kun Zhang

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 467-486, 2024, DOI:10.32604/cmc.2024.051426

    Abstract To address the challenges of missed detections in water surface target detection using solely visual algorithms in unmanned surface vehicle (USV) perception, this paper proposes a method based on the fusion of visual and LiDAR point-cloud projection for water surface target detection. Firstly, the visual recognition component employs an improved YOLOv7 algorithm based on a self-built dataset for the detection of water surface targets. This algorithm modifies the original YOLOv7 architecture to a Slim-Neck structure, addressing the problem of excessive redundant information during feature extraction in the original YOLOv7 network model. Simultaneously, this modification simplifies… More >

  • Open Access

    ARTICLE

    SMSTracker: A Self-Calibration Multi-Head Self-Attention Transformer for Visual Object Tracking

    Zhongyang Wang, Hu Zhu, Feng Liu*

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 605-623, 2024, DOI:10.32604/cmc.2024.050959

    Abstract Visual object tracking plays a crucial role in computer vision. In recent years, researchers have proposed various methods to achieve high-performance object tracking. Among these, methods based on Transformers have become a research hotspot due to their ability to globally model and contextualize information. However, current Transformer-based object tracking methods still face challenges such as low tracking accuracy and the presence of redundant feature information. In this paper, we introduce self-calibration multi-head self-attention Transformer (SMSTracker) as a solution to these challenges. It employs a hybrid tensor decomposition self-organizing multi-head self-attention transformer mechanism, which not only… More >

  • 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… 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… 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… 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 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 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 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… 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 More >

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