Results 11 to 20 of about 8,015,933 (303)
From target tracking to targeting track: A data-driven yet analytical approach to joint target detection and tracking [PDF]
Signal Processing, 2023 This paper addresses the problem of real-time detection and tracking of a non-cooperative target in the challenging scenario with almost no a-priori information about target birth, death, dynamics and detection probability. Furthermore, there are false and missing data at an unknown yet low rate in the measurements.
Tiancheng Li 0002, Yan Song, Hongqi Fan
openaire +3 more sources
Orthogonal Single-Target Tracking
IEEE Access, 2022 In this study, we propose a novel Wasserstein distributional tracking method that can balance approximation with accuracy in terms of Monte Carlo estimation.
Youjin Kim, Junseok Kwon
doaj +2 more sources
Long short-term memory-based deep recurrent neural networks for target tracking
Information Sciences, 2019 Target tracking is a difficult estimation problem due to target motion uncertainty and measurement origin uncertainty. In this paper, we consider the target tracking problem in the presence of only target motion uncertainty. The traditional approaches to
Chang Gao, Junkun Yan
exaly +2 more sources
Underwater Acoustic Target Tracking: A Review
Sensors, 2018 Advances in acoustic technology and instrumentation now make it possible to explore marine resources. As a significant component of ocean exploration, underwater acoustic target tracking has aroused wide attention both in military and civil fields.
Junhai Luo
exaly +2 more sources
Computer vision based obstacle detection and target tracking for autonomous vehicles [PDF]
MATEC Web of Conferences, 2021 Obstacle detection and target tracking are two major issues for intelligent autonomous vehicles. This paper proposes a new scheme to achieve target tracking and real-time obstacle detection of obstacles based on computer vision.
Fang Ruoyu, Cai Cheng
doaj +1 more source
Transformer-Based Maneuvering Target Tracking
Sensors, 2022 When tracking maneuvering targets, recurrent neural networks (RNNs), especially long short-term memory (LSTM) networks, are widely applied to sequentially capture the motion states of targets from observations. However, LSTMs can only extract features of
Guanghui Zhao +4 more
doaj +1 more source
Tracking of interacting targets [PDF]
2017 20th International Conference on Information Fusion (Fusion), 2017 In this paper we present a method for the tracking of interacting targets disregarding whether or not the targets are close to each other. The method relies on parametric modeling of assumptions about targets interactive motion. Our filtering solution incorporates the parameters of the model in the state vector to perform on-line parameter estimation ...
Leon, C.M. +2 more
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IEEE Access, 2023 Due to their distinctive features, unmanned aerial vehicles (UAVs) have been recently exploited to support a wide range of applications. The features include low maintenance cost, compact size, and excellent capability of maneuvering. In particular, UAVs
Mohannad Alhafnawi +6 more
semanticscholar +1 more source
Science, Technology, & Human Values, 2017 This introduction to the special issue of the same title sets out the context for a critical examination of contemporary developments in sociotechnical systems deployed in the name of security. Our focus is on technologies of tracking, with their claims to enable the identification of those who comprise legitimate targets for the use of violent force ...
Lucy Suchman +2 more
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Multi-Agent Reinforcement Learning Aided Intelligent UAV Swarm for Target Tracking
IEEE Transactions on Vehicular Technology, 2022 Past few years have witnessed the widespread adoption of unmanned aerial vehicles (UAVs) in target tracking for regional monitor and strike. Most existing target tracking approaches rely on the target motion frames obtained by the camera equipped, or on ...
Zhaoyue Xia +6 more
semanticscholar +1 more source