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Conventional vision-based sensors face limitations such as low update rates, restricted applicability, and insufficient robustness in dynamic environments with complex object motions. Single-pixel tracking systems offer high efficiency and minimal data redundancy by directly acquiring target positions without full-image reconstruction. This paper proposes a single-pixel detection system for adaptive multi-target tracking based on the geometric moment and the exponentially weighted moving average (EWMA). The proposed system leverages geometric moments for high-speed target localization, requiring merely 3N measurements to resolve centroids for N targets. Furthermore, the output values of the system are used to continuously update the weight parameters, enabling adaptation to varying motion patterns and ensuring consistent tracking stability. Experimental validation using a digital micromirror device (DMD) operating at 17.857 kHz demonstrates a theoretical tracking update rate of 1984 Hz for three objects. Quantitative evaluations under 1920 × 1080 pixel resolution reveal a normalized root mean square error (NRMSE) of 0.00785, confirming the method's capability for robust multi-target tracking in practical applications.
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http://dx.doi.org/10.3390/s25133879 | DOI Listing |
Animals (Basel)
August 2025
Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
With the development of precision livestock farming, in order to achieve the goal of fine management and improve the health and welfare of dairy cows, research on dairy cow motion monitoring has become particularly important. In this study, considering the problems surrounding a large amount of model parameters, the poor accuracy of multi-target tracking, and the nonlinear motion of dairy cows in dairy farming scenes, a lightweight detection model based on improved YOLO v11n was proposed and four tracking algorithms were compared. Firstly, the Ghost module was used to replace the standard convolutions in the YOLO v11n network and a more lightweight attention mechanism called ELA was replaced, which reduced the number of model parameters by 18.
View Article and Find Full Text PDFBMC Sports Sci Med Rehabil
August 2025
Department of Athletic Training, Shanxi Sports Vocational College, Taiyuan, 030024, China.
Background: The integration of deep learning techniques into sports performance analysis has significantly advanced athlete monitoring, motion tracking, and predictive modelling. These advancements have significantly improved the ability to assess performance, optimize training strategies, and reduce injury risks. However, despite notable progress, challenges remain in standardizing methodologies, ensuring model reliability, and enhancing real-time application across various sports disciplines.
View Article and Find Full Text PDFMikrochim Acta
August 2025
Key Laboratory of Drug Quality Control and Pharmacovigilance, Ministry of Education, School of Pharmacy, China Pharmaceutical University, 210009, Nanjing, China.
Precise and sensitive detection of cancer biomarkers is essential for early diagnosis and effective treatment. However, most existing sensing strategies rely on single targets, which may lack the specificity required for accurate disease diagnosis. To address this limitation, we propose an AND-gate logic DNA walker capable of simultaneously detecting two distinct types of biomarkers: miRNA-21 and flap endonuclease 1 (FEN1).
View Article and Find Full Text PDFISA Trans
July 2025
Key Laboratory of Intelligent Control and Decision of Complex Systems, School of Automation, Beijing Institute of Technology, Beijing 100081, China; School of Automation, Zhongyuan University of Technology, Zhengzhou 450007, China. Electronic address:
In the multi-target tracking (MTT) problem of sensor networks, inconsistencies in sensor fields of view and target labeling can significantly degrade tracking accuracy. These issues are particularly acute in clustered sensor networks. So, this paper presents an MTT algorithm to address the tracking problem in clustered sensor networks with the aforementioned two issues.
View Article and Find Full Text PDFPhytomedicine
September 2025
Department of Molecular and Life Science, Hanyang University, Ansan 15588, Republic of Korea; Department of Medicinal and Life Science, Hanyang University, Ansan 15588, Republic of Korea; Department of Molecular Medicine, School of Biopharmaceutical Convergence, Ansan 15588, Republic of Korea. Elect
Background: Phytochemicals exhibit multi-target therapeutic potential with low toxicity, but their clinical translation is limited by poor bioavailability, unclear mechanisms, inadequate models, and structural instability. Addressing these barriers requires integrated strategies that preserve structure-function integrity and improve translational fidelity.
Purpose: This review identifies key translational barriers of phytochemicals and proposes integrated, structure-informed strategies combining delivery systems, mechanistic insights, and advanced models to preserve structure-function integrity and enable their application in precision medicine.