Multi-Sensor Data Fusion with a Reconfigurable Module and Its Application to Unmanned Storage Boxes [PDF]
Sensors, 2022 We present a multi-sensor data fusion model based on a reconfigurable module (RM) with three fusion layers. In the data layer, raw data are refined with respect to the sensor characteristics and then converted into logical values. In the feature layer, a
Sung-Kyu Lee +3 more
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High-Precision 3D Reconstruction in Complex Scenes via Implicit Surface Reconstruction Enhanced by Multi-Sensor Data Fusion [PDF]
SensorsIn this paper, we investigate implicit surface reconstruction methods based on deep learning, enhanced by multi-sensor data fusion, to improve the accuracy of 3D reconstruction in complex scenes.
Quanchen Zhou +3 more
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Multi-Sensor Data Fusion for Future Telematics Application [PDF]
Journal of Astronomy and Space Sciences, 2003 In this paper, we present multi-sensor data fusion for telematics application. Successful telematics can be realized through the integration of navigation and spatial information.
Seong-Baek Kim +4 more
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A Review of Multi-Sensor Fusion SLAM Systems Based on 3D LIDAR
Remote Sensing, 2022 The ability of intelligent unmanned platforms to achieve autonomous navigation and positioning in a large-scale environment has become increasingly demanding, in which LIDAR-based Simultaneous Localization and Mapping (SLAM) is the mainstream of research
Xiaobin Xu +7 more
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Tracking filter and multi-sensor data fusion [PDF]
Sadhana, 2000 In this paper factorization filtering, fusion filtering strategy and related algorithms are presented.
Appavu, Raj R +3 more
core +3 more sources
Multi-Sensor Fusion in Automated Driving: A Survey
IEEE Access, 2020 With the significant development of practicability in deep learning and the ultra-high-speed information transmission rate of 5G communication technology will overcome the barrier of data transmission on the Internet of Vehicles, automated driving is ...
Zhangjing Wang, Yu Wu, Qingqing Niu
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Hybrid Particle Swarm Optimization for Multi-Sensor Data Fusion. [PDF]
Sensors (Basel), 2018 A hybrid particle swarm optimization (PSO), able to overcome the large-scale nonlinearity or heavily correlation in the data fusion model of multiple sensing information, is proposed in this paper. In recent smart convergence technology, multiple similar and/or dissimilar sensors are widely used to support precisely sensing information from different ...
Kim H, Suh D.
europepmc +5 more sources
Advances in Multi-Sensor Data Fusion: Algorithms and Applications [PDF]
Sensors, 2009 With the development of satellite and remote sensing techniques, more and more image data from airborne/satellite sensors have become available. Multi-sensor image fusion seeks to combine information from different images to obtain more inferences than can be derived from a single sensor. In image-based application fields, image fusion has emerged as a
Dong Jiang, Jingying Fu
exaly +4 more sources
Strategies for Class-Imbalanced Learning in Multi-Sensor Medical Imaging [PDF]
SensorsThis narrative critical review addresses class imbalance in medical imaging, particularly within the context of multi-sensor and multi-modal environments, poses a critical challenge to developing reliable AI diagnostic systems.
Da Zhou, Song Gao, Xinrui Huang
doaj +2 more sources
Review of the Method for Distributed Multi-sensor Multi-target Tracking
Leida xuebao, 2023 Multi-sensor multi-target tracking is a popular topic in the field of information fusion. It improves the accuracy and stability of target tracking by fusing multiple local sensor information.
Yajun ZENG +4 more
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