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Journal articles on the topic 'Tracking information'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Kim, Intaek, Malik Muhammad Khan, Tayyab Wahab Awan, and Youngsung Soh. "Multi-Target Tracking Using Color Information." International Journal of Computer and Communication Engineering 3, no. 1 (2014): 11–15. http://dx.doi.org/10.7763/ijcce.2014.v3.283.

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2

Hu, Wei, Armaiti Ardeshiricham, and Ryan Kastner. "Hardware Information Flow Tracking." ACM Computing Surveys 54, no. 4 (2021): 1–39. http://dx.doi.org/10.1145/3447867.

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Information flow tracking (IFT) is a fundamental computer security technique used to understand how information moves through a computing system. Hardware IFT techniques specifically target security vulnerabilities related to the design, verification, testing, manufacturing, and deployment of hardware circuits. Hardware IFT can detect unintentional design flaws, malicious circuit modifications, timing side channels, access control violations, and other insecure hardware behaviors. This article surveys the area of hardware IFT. We start with a discussion on the basics of IFT, whose foundations

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3

The Lancet. "Fast-tracking epidemic information." Lancet 348, no. 9042 (1996): 1599. http://dx.doi.org/10.1016/s0140-6736(96)21050-5.

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4

Henderson, Madeline M. "Tracking nontraditional information systems." Journal of the American Society for Information Science 39, no. 4 (1988): 270–72. http://dx.doi.org/10.1002/(sici)1097-4571(198807)39:4<270::aid-asi6>3.0.co;2-j.

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5

Khan, Malik M., Tayyab W. Awan, Intaek Kim, and Youngsung Soh. "Tracking Occluded Objects Using Kalman Filter and Color Information." International Journal of Computer Theory and Engineering 6, no. 5 (2014): 438–42. http://dx.doi.org/10.7763/ijcte.2014.v6.905.

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6

Huang, Jingbo. "Application of Information Processing System Based on DSP in Electronic Information Engineering." Journal of Physics: Conference Series 2209, no. 1 (2022): 012010. http://dx.doi.org/10.1088/1742-6596/2209/1/012010.

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Abstract On the one hand, target tracking technology is widely used in navigation, guidance, alarm and monitoring and other military fields, on the other hand, it is also widely used in civil fields such as traffic information monitoring and security. This paper mainly studies the application of information processing system based on DSP in electronic information engineering. This paper introduces DSP information processing system in detail. Aiming at the comprehensive requirements of real-time and tracking performance of the target tracking system, multi-feature fusion optimization method is

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7

Willis, Judith B. "Resident Tracking Health Information System." Primary Care: Clinics in Office Practice 12, no. 3 (1985): 497–514. http://dx.doi.org/10.1016/s0095-4543(21)00327-4.

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8

Lee, Jin-Hyung, Seong-Won Jo, Jae-Min Kim, and Sun-Tae Chung. "Object Tracking Using Information Fusion." Journal of Korean institute of intelligent systems 18, no. 5 (2008): 666–71. http://dx.doi.org/10.5391/jkiis.2008.18.5.666.

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9

Lentz, Leo. "Eye-tracking and Information Design." Information Design Journal 13, no. 3 (2005): 255–61. http://dx.doi.org/10.1075/idjdd.13.3.12len.

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10

Grenoble, Lenore. "Discourse Deixis and Information Tracking." Annual Meeting of the Berkeley Linguistics Society 20, no. 1 (1994): 208. http://dx.doi.org/10.3765/bls.v20i1.1447.

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11

Maedche, Alexander. "Web information tracking using ontologies." Intelligent Systems in Accounting, Finance & Management 12, no. 3 (2004): 215–25. http://dx.doi.org/10.1002/isaf.230.

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12

Ding, Feng, and Zhi Hong Ouyang. "Passive Tracking Algorithm with Transmitter Attribute Information." Applied Mechanics and Materials 865 (June 2017): 586–94. http://dx.doi.org/10.4028/www.scientific.net/amm.865.586.

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Traditional passive tracking algorithms are usually subjected to problems such as the poor measurement accuracy of parameters of target motion, complex algorithm, instable tracking precision under complex circumstances. Aiming at this issue, in this paper we combined the dual function of transmitter identification and target tracking in passive reconnaissance, discussed the selection of transmitter eigenvector in passive tracking based on transmitter attribute information, established the passive tracking algorithm framework combined with transmitter attribute information, and then investigate

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13

Fang, Yingwu. "ADAPTIVE VISUAL TRACKING METHOD OF FUSING MULTIPLE INFORMATION." Latin American Applied Research - An international journal 50, no. 1 (2019): 27–32. http://dx.doi.org/10.52292/j.laar.2020.165.

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The objective is to present an adaptive tracking approach of visual objects in the framework of particle filters (PF) and conflict redistribution strategy based on Dezert-Smarandache theory (DSmT). A combination rule of conflict redistribution was introduced into the researches on visual objects tracking, position and color information of moving objects were combined by modified combination strategy information, and the objects tracking model of fusing multiple information on the condition of occluded objects was established effectively. On the basis of building the execution panel of objects

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14

Leng, Yue, and Sheng Zhong. "Objective Prediction Tracking Control Technology Assisted by Inertial Information." Journal of Marine Science and Engineering 11, no. 11 (2023): 2175. http://dx.doi.org/10.3390/jmse11112175.

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This paper addresses the challenge of reduced tracking accuracy in maritime electro-optical tracking equipment when dealing with high-mobility targets like speedboats and aircraft due to off-target error delays. We propose an innovative technique that leverages inertial navigation data to enhance target prediction and tracking control. Our approach involves the real-time integration of high-frequency inertial navigation-derived attitude information into the tracking system. By combining off-target error information with angular measurements from the tracking mechanism, we project the vector of

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15

Raudonis, Vidas, Agnė Paulauskaitė-Tarasevičienė, and Laura Kižauskienė. "The Gaze Tracking System with Natural Head Motion Compensation." Informatica 23, no. 1 (2012): 105–24. http://dx.doi.org/10.15388/informatica.2012.351.

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16

Zhao, Yeli, and Keng Siau. "Cognitive Neuroscience in Information Systems Research." Journal of Database Management 27, no. 1 (2016): 58–73. http://dx.doi.org/10.4018/jdm.2016010103.

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This paper reviews cognitive neuroscience and several neurophysiological tools (e.g., fMRI, PET, EEG, MEG, and eye tracking). The strengths and weaknesses of such tools for information systems research are presented. The paper provides examples of existing cognitive neuroscience studies in varies areas, such as neuroeconomics, neuromarketing, and eye tracking. In addition, this paper provides an overview of brain areas that response to various mental processes, and discusses the localization and functionality of each brain area. Because of the popularity of eye-tracking research in information

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17

Cai, Z., J. Bennett, D. Lu, et al. "BOLUS TRACKING USING LOCAL DENSITY INFORMATION." IFAC Proceedings Volumes 39, no. 18 (2006): 303–8. http://dx.doi.org/10.3182/20060920-3-fr-2912.00056.

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18

Cao, Jie, and Yanlin Li. "Fusion information-based moving tracking algorithm." JOURNAL OF ELECTRONIC MEASUREMENT AND INSTRUMENT 25, no. 3 (2011): 211–17. http://dx.doi.org/10.3724/sp.j.1187.2011.00211.

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19

Klasen, Morris, and Volker Steinhage. "Improving wildlife tracking using 3D information." Ecological Informatics 68 (May 2022): 101535. http://dx.doi.org/10.1016/j.ecoinf.2021.101535.

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20

Levine, William H., and Celia M. Klin. "Tracking of spatial information in narratives." Memory & Cognition 29, no. 2 (2001): 327–35. http://dx.doi.org/10.3758/bf03194927.

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21

V, Mathi Seelan, and Sunitha Abburu. "Multiple Component Based Information Tracking System." International Journal of Computer Science & Engineering Survey 2, no. 2 (2011): 57–67. http://dx.doi.org/10.5121/ijcses.2011.2206.

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22

Sadri, F. "Information source tracking method: efficiency issues." IEEE Transactions on Knowledge and Data Engineering 7, no. 6 (1995): 947–54. http://dx.doi.org/10.1109/69.476500.

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23

Watts, Vabren. "CME Companies Tracking M.D.s’ Personal Information." Psychiatric News 49, no. 3 (2014): 1. http://dx.doi.org/10.1176/appi.pn.2014.2a4.

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24

Shokishalov, Zh, and H. Wang. "Applying Eye Tracking in Information Security." Procedia Computer Science 150 (2019): 347–51. http://dx.doi.org/10.1016/j.procs.2019.02.062.

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25

Berwanger, Dietmar, and Łukasz Kaiser. "Information Tracking in Games on Graphs." Journal of Logic, Language and Information 19, no. 4 (2010): 395–412. http://dx.doi.org/10.1007/s10849-009-9115-8.

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26

Panin, Giorgio, and Alois Knoll. "Mutual Information-Based 3D Object Tracking." International Journal of Computer Vision 78, no. 1 (2007): 107–18. http://dx.doi.org/10.1007/s11263-007-0083-7.

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27

Blair, W. "Target Tracking [Society News & Information]." IEEE Aerospace and Electronic Systems Magazine 22, no. 6 (2007): 37–38. http://dx.doi.org/10.1109/maes.2007.383963.

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28

Ren, Jinfu, Yang Liu, and Jiming Liu. "Chaotic behavior learning via information tracking." Chaos, Solitons & Fractals 175 (October 2023): 113927. http://dx.doi.org/10.1016/j.chaos.2023.113927.

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29

ZHANG, XIAOYAN, and TING WANG. "TOPIC TRACKING WITH IMPROVED REPRESENTATION MODEL AND JOINT TRACKING METHOD." International Journal of Wavelets, Multiresolution and Information Processing 08, no. 06 (2010): 913–30. http://dx.doi.org/10.1142/s0219691310003869.

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Topic tracking is to monitor a stream of stories to find additional stories on a topic identified by several samples. However, the predefined information about a tracked topic does not provide enough information to deal with the new information occurred in the tracking procedure. To overcome this problem, we proposed a joint tracking method using both the topic-specific information from the predefined information and the non-topic-specific information from the data on other topics. Besides, to overcome the limitation of the representation model and the topic drift problem, we have also used tw

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30

Zhao, Lan, and Tao Zeng. "Target Recognition Application of Real-Time Optical Information Processing System." Applied Mechanics and Materials 536-537 (April 2014): 197–200. http://dx.doi.org/10.4028/www.scientific.net/amm.536-537.197.

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This paper focuses on the visual tracking algorithm in optical imaging surveillance and tracking system. The tracking particle filter framework deemed find sparse representation problem, can effectively overcome the visual tracking algorithm appears in noise, occlusion, background interference and complex situations such as illumination changes. Morphological methods using digital occlusion area is detected to determine whether the date is added to the template tracking results set, thereby updating the control template, to effectively prevent the drift tracking results.

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31

Li, Shuxiao, Ou Wu, Chengfei Zhu, and Hongxing Chang. "Visual object tracking using spatial Context Information and Global tracking skills." Computer Vision and Image Understanding 125 (August 2014): 1–15. http://dx.doi.org/10.1016/j.cviu.2013.10.001.

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32

Yang, Yifan, Ziqi He, Jiaxu Wan, et al. "FusionTrack: Multiple Object Tracking with Enhanced Information Utilization." Applied Sciences 13, no. 14 (2023): 8010. http://dx.doi.org/10.3390/app13148010.

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Multi-object tracking (MOT) is one of the significant directions of computer vision. Though existing methods can solve simple tasks like pedestrian tracking well, some complex downstream tasks featuring uniform appearance and diverse motion remain difficult. Inspired by DETR, the tracking-by-attention (TBA) method uses transformers to accomplish multi-object tracking tasks. However, there are still issues with existing TBA methods within the TBA paradigm, such as difficulty detecting and tracking objects due to gradient conflict in shared parameters, and insufficient use of features to disting

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33

Lund, Haakon. "Eye tracking in library and information science: a literature review." Library Hi Tech 34, no. 4 (2016): 585–614. http://dx.doi.org/10.1108/lht-07-2016-0085.

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Purpose The purpose of this paper is to present a systematic literature review of the application of eye-tracking technology within the field of library and information science. Eye-tracking technology has now reached a level of maturity, which makes the use of the technology more accessible. Subsequently, a growing interest in employing eye tracking as a methodology within library and information science research must be anticipated. Design/methodology/approach The review follows the guidelines set in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses recommendations. Two

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34

Kuznietsov, Oleksandr, Oleksii Kolomiitsev, Volodymyr Karlov, Dmytro Kuznietsov, and Volodymyr Timofeyev. "IMPROVING THE ACCURACY OF EXPONENTIAL SMOOTHING IN SECONDARY INFORMATION PROCESSING IN MODERN INFORMATION LOCATION SYSTEMS." Advanced Information Systems 9, no. 2 (2025): 93–101. https://doi.org/10.20998/2522-9052.2025.2.12.

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The quality of tracking location objects (LO) depends not only on their ability to perform complex maneuvering, but also on the influence of external conditions of the primary processing of location information (LI). These external conditions can be defined as the state of the atmosphere and the influence of the earth (sea) surface. The quality of secondary processing of LO, in particular, the stability of tracking depends on the accuracy of the current measurement of the radial velocity of the observation object (OO), which is largely determined by the influence of the external conditions of

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35

Botterill, K., R. Allen, and P. McGeorge. "Multiple-Object Tracking." Experimental Psychology 58, no. 3 (2011): 196–200. http://dx.doi.org/10.1027/1618-3169/a000085.

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The Multiple-Object Tracking paradigm has most commonly been utilized to investigate how subsets of targets can be tracked from among a set of identical objects. Recently, this research has been extended to examine the function of featural information when tracking is of objects that can be individuated. We report on a study whose findings suggest that, while participants can only hold featural information for roughly two targets this task does not affect tracking performance detrimentally and points to a discontinuity between the cognitive processes that subserve spatial location and featural

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36

Duranceau, Ellen Finnie. "License Tracking." Serials Review 26, no. 3 (2000): 69–73. http://dx.doi.org/10.1080/00987913.2000.10764606.

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37

Stam, Deirdre C. "Tracking art historians: on information needs and information-seeking behaviour." Art Libraries Journal 14, no. 3 (1989): 13–16. http://dx.doi.org/10.1017/s0307472200006349.

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The information-gathering activities of art historians have been studied from three different perspectives: in terms of the books they use; through their own accounts of their working processes; and by informal, systematic observation, written up as ‘user studies’, by art librarians. While observation implies objectivity, a distance between observer and observed, in practice art librarians are very much involved with the art historian in the work of art history and in the development of its methodologies.

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38

Li, Zhi Gang, and Han Lin Zhang. "An Approach to Estimating Acceleration Information for Longitudinal Control." Applied Mechanics and Materials 341-342 (July 2013): 1191–96. http://dx.doi.org/10.4028/www.scientific.net/amm.341-342.1191.

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Most of control systems choose velocity and distance as the control parameters for vehicle longitudinal control in the case where no inter-vehicle communication is available and have poor response capability under urgent conditions. The purpose of this paper is to propose new approach to estimating relative acceleration information for vehicle longitudinal control without inter-vehicle communication. Approach is based on design tracking differentiator to filtering and estimating velocity and relative acceleration signal. But for traditional tracking differentiator with many parameters, the tri

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39

Wu, Xiao-Jia, Meng Han, Yan-Long Li, et al. "Information-Enhance Twofold Siamese Tracker for Video Target Tracking." Journal of Computers 36, no. 3 (2025): 1–15. https://doi.org/10.63367/199115992025063603001.

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The current video target-tracking networks, for example, SiamFC, SiamRPN, or C-RPN, correlation between the target features in a video sequence is not fully considered in the extracted tracking target features. Consequently, ability to express features of the target is weak, the tracking precision is low, and the interference capability of factors such as background clutter or scale change is poor. In this paper, we propose an information-enhanced twofold Siamese tracker (IETST) to enable the target information to learn the robust features of the target appearance in a twin-network tracker. Th

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40

Xu, Yue, Hang Yin, and Yuanming Zhao. "Research on Multi-Channel Information Tracking Method." Academic Journal of Science and Technology 2, no. 2 (2022): 149–53. http://dx.doi.org/10.54097/ajst.v2i2.1304.

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This project provides a trajectory tracking method, device and computer storage medium, including associating the bottom database features of each target object with at least one trajectory feature to construct the identity association information of each target object; According to at least one track feature of each target object, each detection feature obtained from different target videos is identified, and the target object corresponding to each detection feature is determined; According to the identity association information of each target object and the target object of each detection f

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41

Xuan, Shujin. "The Impact of Analyst Following on Accounting Information Quality." SHS Web of Conferences 218 (2025): 04021. https://doi.org/10.1051/shsconf/202521804021.

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This article mainly discusses the impact of analyst tracking on accounting information quality based on the background of analyst tracking and accounting information quality. However, the specific path of the interaction between the two and the mechanism of their impact on the capital market have not been fully revealed in existing research. This study seeks to address these gaps by examining how analyst tracking impacts the quality of accounting information and exploring the regulatory and feedback effects of their interaction on the capital market.Specific problem analysis is conducted on th

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42

Li, Jing, and Guangren Zhou. "Visual Information Features and Machine Learning for Wushu Arts Tracking." Journal of Healthcare Engineering 2021 (August 4, 2021): 1–6. http://dx.doi.org/10.1155/2021/6713062.

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Martial arts tracking is an important research topic in computer vision and artificial intelligence. It has extensive and vital applications in video monitoring, interactive animation and 3D simulation, motion capture, and advanced human-computer interaction. However, due to the change of martial arts’ body posture, clothing variability, and light mixing, the appearance changes significantly. As a result, accurate posture tracking becomes a complicated problem. A solution to this complicated problem is studied in this paper. The proposed solution improves the accuracy of martial arts tracking

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43

Han, Zhifeng, and Zheng Fang. "A filter algorithm for receiver tracking loops assisted by inertial information." Journal of Navigation 75, no. 2 (2021): 496–506. http://dx.doi.org/10.1017/s0373463321000916.

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AbstractIn traditional satellite navigation receivers, the parameters of tracking loop such as loop bandwidth and integration time are usually set in the design of the receivers according to different scenarios. The signal tracking performance is limited in traditional receivers. In addition, when the tracking ability of weak signals is improved by extending the integration time, negative effect of residual frequency error becomes more and more serious with extension of the integration time. To solve these problems, this paper presents out research on receiver tracking algorithms and proposes

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44

Sukkar, Majdi, Madhu Shukla, Dinesh Kumar, Vassilis C. Gerogiannis, Andreas Kanavos, and Biswaranjan Acharya. "Enhancing Pedestrian Tracking in Autonomous Vehicles by Using Advanced Deep Learning Techniques." Information 15, no. 2 (2024): 104. http://dx.doi.org/10.3390/info15020104.

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Effective collision risk reduction in autonomous vehicles relies on robust and straightforward pedestrian tracking. Challenges posed by occlusion and switching scenarios significantly impede the reliability of pedestrian tracking. In the current study, we strive to enhance the reliability and also the efficacy of pedestrian tracking in complex scenarios. Particularly, we introduce a new pedestrian tracking algorithm that leverages both the YOLOv8 (You Only Look Once) object detector technique and the StrongSORT algorithm, which is an advanced deep learning multi-object tracking (MOT) method. O

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45

Lam, Sze-Ying, and Alexandre Zénon. "Information Rate in Humans during Visuomotor Tracking." Entropy 23, no. 2 (2021): 228. http://dx.doi.org/10.3390/e23020228.

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Previous investigations concluded that the human brain’s information processing rate remains fundamentally constant, irrespective of task demands. However, their conclusion rested in analyses of simple discrete-choice tasks. The present contribution recasts the question of human information rate within the context of visuomotor tasks, which provides a more ecologically relevant arena, albeit a more complex one. We argue that, while predictable aspects of inputs can be encoded virtually free of charge, real-time information transfer should be identified with the processing of surprises. We form

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46

Jung Yee, Kim. "Positional Tracking System Using Smartphone Sensor Information." Journal of Multimedia Information System 6, no. 4 (2019): 265–70. http://dx.doi.org/10.33851/jmis.2019.6.4.265.

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47

Park, Jongsoon. "Information Architecture Design Using Eye-tracking Method." Journal of the HCI Society of Korea 2, no. 1 (2007): 33. http://dx.doi.org/10.17210/jhsk.2007.05.2.1.33.

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48

Van Keuk, G. "Multihypothesis tracking using incoherent signal-strength information." IEEE Transactions on Aerospace and Electronic Systems 32, no. 3 (1996): 1164–70. http://dx.doi.org/10.1109/7.532278.

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49

YOSHIMOTO, KEN-ICHI, HIDEKI OGAWA, and HIROSHI KUBOTA. "Course Tracking Control Algorithm Using Visual Information." Vehicle System Dynamics 28, no. 6 (1997): 385–98. http://dx.doi.org/10.1080/00423119708969363.

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50

Kulmer, Josef, Erik Leitinger, Stefan Grebien, and Klaus Witrisal. "Anchorless Cooperative Tracking Using Multipath Channel Information." IEEE Transactions on Wireless Communications 17, no. 4 (2018): 2262–75. http://dx.doi.org/10.1109/twc.2018.2790936.

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